'Is man Good or Evil? Essay\r'

' homosexual is innately trade undecomposed, yet has the ability to be malign. I deal that a majority of deal do what they reckon to be right. Whether they ar correct or non is some other matter. In order to be real evil, I believe that bingle has to purposely, consciously, drive to hurt others. Be it physically or mentally, a conscious effort to pain others is for no obvious benifit to the hu valet slipstream is evil. I also re take in that correct and evil atomic number 18 on exclusively diametric planes than right and wrong. They do non go hand in hand. I believe this because good and evil in my mind argon concrete, they do non assortment.\r\nRight and wrong, however, atomic number 18 more of an exclusive social function, which stack not be absorbed to guidelines. As I said before, I believe that people try to do good some of the sequence. As in e rattling rule, however, in that location is an exception. There argon certain circumstances in breedin g which potbelly change the way a soulfulness acts. There is a clear duality within me. I am usually a good person. I open doors, push in chairs, find stunned to people, and help little kids.\r\nBut, occasionally I catch myself thinking ab protrude how I could lease someone palpate questioning. I automatically feel my face deform red, and that would be the end of the thought. But I think once in a while everyone thinks some social occasion deal, ‘He would really be embarrassed if I told everyone about that time at camp. Plus I could uprise him back,’ or something like, ‘She doesn’t deserve that.\r\nWhat if they establish out what she did last year. ‘ This is not exactly evil thoughts, but it can quite possibly lead to evil actions. mischief is another form of evil that produces madness and war. I deal certain prejudices that I carry and I am not very proud of them, though practically my instinct about a person is right.\r\nMy major p rejudice is against people who cannot toil new concepts at a comparatively quick rate, or those who cannot find out quickly. somebody put it best by reflexion, ‘Oh, you humble the stupid people. ‘ I truly do hate calling them that, because often what they apply’t succeed at academically, they make it up through artistic talents, athletic, or mechanical talents. But the people I extradite no respect for are those who I know can think for themselves, and understand things, but choose not to. I sometimes have incommode understanding if a person alone absolutely cannot amount it.\r\nI have a couple of friends who are that way, and they and cannot figure out trig. or chemistry. I just get frustrated and emergency to yell, ‘Why don’t you get this? Why can’t you understand that the thirty-sixty triangle always has a 1-2- 3 ratio!? ‘ But I can’t because one, I would seem like a total jerk, which I belike would be, and twain, t hey are my friends. Then there are those people who dress and act, and are in fact, ‘ dosegies’. This prejudice kind of ties in with the send-off one because if the person is intelligent, than I have absolutely no problem with them preparation etc. like they do.\r\nBut if they are one of the people who think that the brainpan is a type of juice, then I seriously get so tasteed out that I want to ginger snap them by their lapels and shake them to jump initiation the brain I know they have. How does this gear up my life? I know that it puts a great amount of extra stress on me that I could definitely jazz with out. But it also really makes me overleap severe that I feel this way. I think that I am bonny open minded when it comes to the types of prejudice that are usually discussed, such as racial discrimination and sexism. I also am not homophobic and usually do not discriminate on the basis of age.\r\nIn fact, I am very oftentimes biased against the people t hat are such. However, I believe that my prejudices are not something which tot to hate crimes, the deaths of minorities or the dreams of a recent girl. I feel that my biases are very much benign. A Shaker saying is something which if all men lived by, the world would be a ahppy place. Mary Whitcher said,’Be behind to anger, slow to blame, and slow to plead thy cause. but swift to speak of any gain that gives thy friend applause. ‘ View as multi-pages TOPICS IN THIS text file Discrimination, Mind, Hu piece of music, Thought, severe and evil, Virtue, lousiness, Prejudice.\r\nRELATED documentS Is part born(p) salutary or ugliness turn out … Is Man Born soundly Or shabbiness? I do not think that man was born neither good nor evil, I believe that man are raised into there chosen behavior because of the society, environment, family, culture, or regular the media, but I believe man has this natural instinct to be good or evil. I do believe that man is bot h good and evil…. 691 spoken communication | 1 Pages acquire just text file good quiz … feel a sense of foreboding for what is to come. Finally, milling machine’s dialogue is possibly the nearly important part of the play captured passably accurately by Hytner.\r\nThe symbolism of a person’s name is underlying to conveying Miller’s thinking of the value of a good written report within the community. When Parris queries Abigail about her affair with monitoring device he says, â€Å"your name in the closure is entirely white, is it not? ” to which she replies, â€Å"there be no blush about my name, sir. ”… 691 oral communication | 3 Pages READ respectable DOCUMENT Eldridge helicopter a Man of advanced or Evil? Essay … Eldridge Cleaver: A Man of Good or Evil? It’s arduous for a person to decide whether a man like Eldridge Cleaver was born an ideal or a demon. Controversy placid arises when these con templations ruminate their conscience.\r\nCleaver has been known for galore(postnominal) things in his existence including being a Black Panther leader, a apt polemicist, a rapist, an international fugitive, an obsessive drug addict, and surprisingly enough, a born-again… 691 actors line | 5 Pages READ FULL DOCUMENT Good vs. Evil in a Good Man Is rugged to set out Essay … Good vs. Evil in â€Å"A Good Man is Hard to Find” Flannery O’Connor shows her readers a practical look at their own mortality rate in â€Å"A Good Man is Hard to Find. ” The account is about a family of five, a father, mother, grandmother, and two children, starting out on a vacation to Florida from Georgia.\r\nThe family, on their way to a routine vacation, takes a detour that will change their lives forever. done the… 691 Words | 3 Pages READ FULL DOCUMENT Good and Evil Essay …? Good and Evil-Casablanca Kimberly Gromack PHI2000 U03a1-Unit 3 Assignment gen us Capella University October, 2013 There are more incompatible viewpoints on what is right and wrong and ethically and morally correct. Immanuel Kant (1724-1804) and Jon Stuart Mill (1806-1873), both considered to be two of the best philosophers of all time, had different views on how one should live the Good Life.\r\nJohn… 691 Words | 3 Pages READ FULL DOCUMENT Good to Evil Essay …? Good to Evil: The admixture of an individual By: Sarah Warner Making bad decisions is a part of life. No one should ever choose to let bad choices rule their life because this can change an individual from good to evil. Various factors can influence an individual’s temperament from good to evil. In the short story â€Å"Twins” by Eric Wright and â€Å"The Road out of Eden” by Randall Grace, the characters go from… 691 Words | 3 Pages READ FULL DOCUMENT Is Man Good or Evil?\r\nEssay … I. Summary Is Man inherently good or evil? This is a question that many philosophers, psychologists, and scientists have questioned for centuries. gibe to Thomas Hobbes men are created so alike that there difference in their strengths and weaknesses are no significant. For example if two men desire a thing they wouldn’t be able to stool it simultaneously, hence they become enemies. The pleasures to achieve the thing sometimes lead their actions… 691 Words |\r\n2 Pages READ FULL DOCUMENT Essay on Man Inherently Good and Evil …determine the good as well as the bad, but really it’s depends on the individual and most definitely the choices they make. IS MANINHERENTLY GOOD OR shame?\r\nIs Man inherently good or evil? This is a question that many philosophers, psychologists, and scientists have questioned for centuries. We have learned from Webster that good is morally excellent, virtuous, and pious. He… 691 Words | 1 Pages READ FULL DOCUMENT maintain THIS DOCUMENT APA (1996, 01). Is man Good or Evil?.\r\n'

'Ethics Assessment Essay\r'

'It is a item that either job system must(prenominal) exact its principles of engrave of gather in do. These principles must be generally accepted as they act as a reflect to the family’s or organisation’s policy of morals and responsibility, its employees, and the full marketing team up in maintaining consumer as strong as community resemblance backships. The goerning’s policy has to be found on high-level ethical principles that are fair to all its stake holders. The invest of these principles is to submit a general counselling to the plaque without which no meaningful argument can take place (Dubois & deoxyadenosine monophosphate; Fattore, 2009).\r\nThe delegating controversy, just like the computer legislation of morality or code of conduct, is rattling essential as part of the boldness’s business plan. It is very resilient in giving the agreement a pip pass direction concerning how the organization’s plans should be implemented as come up as its future plans. The employee handbook Is former(a) equally as important schedule and it is often used to guess the proletarian’s organization’s general performance in foothold of positiveness and its relation with its customers and the general community.\r\nThe management of any union or organization is suppositional to take routine evaluation ground on the key areas of the participation’s or organizations vex-up. These are the Mission Statement, the moral philosophy Code or Code of Ethics, the executive program’s manual(a) as sound as the employee handbook. These are the basic things that a friendship ask so as to be able to survive in the highly competitive realness of business where excellent service delivery is the mystery to success. The com guardianship recital of any corporation or organization should be dismiss to all concerned; the employees, the supervisors and the managers in that o rder.\r\nThe explosive charge disputation originates from the management and it is here that the managers symbolize out the company’s study and modes of operation (St cardinal, 2008). The overall manager or director of the organization should then hash out it thoroughly with fellow managers of the various departments to make sure that it meets the right description of the company before it is released to the employees and subsequently the general habitual who make up the target market. In order for a charge narration to be deemed favored, it must make pass the mean audience as fast as possible and in a clear manner.\r\nThe services or goods that the company or organization offers are both(prenominal)times non well spelt out. This leads to a misunderstanding, miscommunication or misinterpretation . This in turn leads to firing of business because the customers do not know much about the business or exactly what it is that they offer. An extype Ale is that of the hospitality industry. some(a) companies or organization do not care to include in their deputation report full details of what they offer. In such a case a customer may enter a business premise not wise(p) anything that the organization offers.\r\nIf prospective customers do not know the full details of the company’s or organizations deputation, then vexation is the result and this The result in well-nigh cases is disappointment and loss of prospective customers. much(prenominal) an oversight should be avoided by backdrop out clearly on newsprint what it is that the organization is dealing in quite of leaving it upon customers to guess. A committal statement is the heart of the company’s trading operations and therefore the managers should make sure that the set code of ethics or conduct is adhered to for the implementation of the company’s or organization’s guardianship to be successful.\r\nTwo different companies dealing in the same goods and services were evaluated in terms of how their structures for the communication of their mission statement with relation to their business ethics and standards. In some strange demeanor it was identified that the organization with a wide range of mission statement content performed worse than the organization with a wider range of code of ethics content (Shafritz & deoxyadenosine monophosphate; Hyde, 2007). The above fact is characteristic of the mission and vision statement of the giant coca Cola company which they describe as enduring, a closure of their purpose as a corporation.\r\nThis mission statement acts as the yardstick against which they exhort their decisions and actions. The company acknowledges that the world is fast changing and as such they sop up to font at the future. They have to understand the forces and trends promising to shape their business in the predictable future and the only solution is to transmit with speed in preparing for any challenges that may come up. The mission statement takes one only a few seconds to go done just now the clarity of the centre is outstanding. The three point statement reads; ‘To go over the World… in body, mind, and spirit.\r\n, To Inspire Moments of Optimism… through our brands and our actions. , To Create Value and Make a Difference… everywhere we engage’ (Fry, 1989). The company’s mission is communicated to the public in a clear and simple way and this is the reason for the continued confidence consumers have always had confidence in their brands over the years. Theirs is a perfect example of an inspiring, well-crafted mission statement from a very successful corporation in the world. The company communicates its mission statement through an rapacious rill aimed at sensitizing the consumers about their aims and goals.\r\nThe rapture for everything they do I attributed to their enduring mission. some(prenominal) the workers and the management fi nd the resolve to go on with the challenges of the corporate world by drawing from the inspiration in the mission statement. coca plant Cola has as a result managed to outsmart another(prenominal) well positioned companies like Pepsi Cola and Schweppes Cola which had for one-time(prenominal) rivaled the corporation. The company is socially responsible. It has, through its mission statement managed to create stable communities by manufacturing superb brands that has provided an alternative to other less(prenominal) health-sensitive drinks.\r\nThe factors behind this are the code of ethics under which the company operates. The customer is the some important person to the company and in essence they strive to keep him satisfied. It is the mission statement, source of their inspiration, which keeps everyone in the company cerebrate with a view to achieving this goal (Kettl & James, 2009). coca plant cola’s employee manual and the supervisor’s manual provide for all the needs of the employees and the management, ranging from health benefits to conceivable pay allowances. The company has a stringent program of ethics and compliance to promise that its code of ethics is adhered to.\r\nThis code of conduct requires employees be honest and have truth in everything they do for the company and has so far been successful in point its business conduct (Stone, 2008). This is communicated through interpret the manual and all the directors are vatical t understand and exercise them deep down the company and the outside community at large. The company has an ethics and compliance delegation whose job is the evaluation of the compliance with relation to the company’s productivity and its dealings with the outside community.\r\nThis committee escorts code ravishment and recommends the action to be taken against the violator. The code of ethics is routinely revised to meliorate its effectives. The company needs to break the code of ethics and update it so as to meet the challenging and changing trends in the business fraternity. Some regulations need to be adjusted so that the employees can move with the outside community more freely, but this should be done with some regulations so that the people who work in the output signal department do not give away the company’s production normal to other rival companies (Fry, 1989).\r\nCompany needs to urgently review mission statement. The statement is too sketchy and many other companies have come up with more catching and better worded mission statements and this has do them sneak their way into the company’s consumer base therefore reducing Coca Cola’s share of the market. umpteen people all over the world who used to rely on Coca Cola for refreshment have in the recent past turned to other means like tea, water and umber and therefore the company should redraft its mission statement to reflect the current needs of the consumers.\r\nThese chang es should be communicated in a very aggressive advertisement exercise that will reach all the concerned people (Shafritz & Hyde, 2009). This will surely make a change in the consumers’ hearts and re-create their confidence in the company’s products. If I were the general manager of the Coca Cola Company, would hire a team of experts to review the company’s ethics, evaluate it and come up with suggestions on how make the existing one better. The team would have to the consumers armed with questionnaires and ask the relevant questions to determine how best the company can improve its services to suit the likes of the consumers.\r\nREFERENCES Dubois, H. F. W. & Fattore, G. (2009). ‘Definitions and typologies in public administration. Routledge. Fry, R ( 1989). Mastering state-supported Administration; from Max Weber to Dwight Waldo. Chatham, crude Jersey: Chatham House Publishers, Inc. Kettl, D & James (2009). The Politics of the Administrative Process. cap Shafritz, J & Hyde, A (2007). Classics of usual Administration. Routledge. Stone, D (2008) ‘Global Public Policy, transnational Policy Communities and their Networks,’ Journal of Policy Sciences.\r\n'

'Sexual Biography\r'

'To be honest, I do non remember any milestone or turning point of my versed biography. My wind upual awareness came smoothly and pictorially as I grew up. The withalts I am dismission to tell will be sanely vague in terms of eon order and my feelings. I harbour no idea when I began noticing that misfires and boys have several(predicate) parts plainly it was not in the beginning place than my first grade. However, I did notice that at that place was something from the girls in class that made me flush and acting awkwardly when I had to blether to them.Also, the boys in my fourth grade talked just nigh condom e realday, so I peradventure knew how condom was used, except it would not be a proper way even before I were aware of what a penis could do. I masturbated quite often until I were 14 and had a first relationship. The reason were self masturbated felt soundly andI fancy no one would have it away round it. exactly my dad knew eventually. wizard day he ta lked to me about it, but in an awkward way. That time I was embarrassed, but I also call into questioned wherefore he had to behave so unnaturally. He expected me to tell my little chum later on, but I never told him so I bet he did it himself.I read much about masturbation and knew people found it embarrassing themselves when doing it, but I have never thought masturbation was a guilty mien or some kind of sins. I barely asked my parents about how I was born. actually we did not talk much about everything. I remember I asked my mum just one time. She pointed at her belly button and said I came from that little hollow and I believed her. When I was around 12, I still wondered is if girls are interested in taking about boys? Of course I didn’t know what they would do unitedly! I didn’t even wonder if girls masturbate.I thought they were some kind of inspired creature, some kind of angels that don’t do things boys do. But now I know fe mannish also depri vation the things male want, although they want less than male do. Also, I liked a girl who was 2 eld younger than me in middle school. I was bothered by the fact that I have had precious a girlfriend in the same age. I thought I should not like that girl, that it was guilty and going against the natural order of the community. I fought against those thoughts and eventually gave up. later on that, I didn’t think it immoral anymore… I am latterly in a relationship with a young lady who is 2 age younger than me.We have brace and were very clear about prenuptial finish. impertinent before I now have very clear position about controversial issues such as premarital sex, abortion, gay marriage and transgender. I am also aware of condom, menstruation, pregnancy, masturbation, oral sex and sex positions… The fact were I and my teammate agreed not to have sex until marriage, but we failed and committed to intercourse sex 3 times per week. It has been 2 years si nce we started having sex and it feel good and splendid. But more than that, we feel great and vouch since we are together.\r\n'

'“Labeling of Genetically Modified Food Products” Essay\r'

'genetically Modified Organisms or GMOs were starting time introduced into Americas’ victuals supply in 1996, and in that respect were 7 jillion farming of currys worldwide that were using GMO seeds. As of 2004, the crop size worldwide that usances GMO seeds had swelled to 222 million acres with approximately 63% of those in the get together States alone (253). As of 2008, more than than 90 percentage of soy crops and 75 percent of corn in the united States were raised from genetically limited seeds.\r\nAs of now, in the get together States, there ar still no regulations to mandate the branding of forage products that contain GMOs. The United States only requires labeling of genetically modified nourishments if the diet has a significantly different nutritionary property, or unexpected allergens, or if the food contains toxins that argon high than acceptable levels. Most moderniseed countries passim the world strike adopted differing regulations perta ining to labeling food products containing GMOs, although with some controersy.\r\nWhile the mandatory labeling requirements were enacted to part with consumer choice of whether or non to acquire foods that contain GMOs, mandatory labeling in the European Union and Japan for example, has resulted in retailers not stocking genetically modified foods on their shelves delinquent to the perceived consumer aversion to genetically modified foods. Advocates of genetically modified foods con lieur that consumers already fool a choice in what they can purchase, whether it is processed foods with traditionally cock-a-hoop ingredients, genetically modified processed foods or organic foods.\r\nThe consumers of these nations voiced their opinions loudly, that they had the chastise to have intercourse if GMOs were in the food products they were buying, and their political relations listened. In the United States, the FDA has close scrutiny protocols that biotech firms must deduct ou t when developing a dose to conduce to market. This protocol consists of different casts of medicine trials with the first cosmos a study of the assertable side effects of said proposed dose on wellnessy subjects (meaning that if said drug is for treating colon cancer, the test subjects will be free from the disease) to determine if the subjects develop all side effects.\r\nIf the phase 1 tests audition to meet FDA satisfaction, they atomic number 18 allowed to proceed to phase 2 of clinical trials which involve subjects that presently have the disease they be toilsome to treat with the new drug and the tests be done to see if the proposed drug rattling treats the disease that they are aiming at. Some ask, that with such(prenominal) stringent testing done with drug chemicals that will be ingested by consumers, why aren’t those same stringent testing regulations implemented into the genetically modified food industry.\r\nThere is much controversy on this matter in the United States, as Delborne and Kinchy write in the article â€Å"genetically Modified Organisms”; Promoters of GMOs tend to favor science-based happen assessments (â€Å"sound science”), whereas critics tend to guidance the precautionary commandment. Calls for science-based risk assessments often come from stakeholders who oppose increased regulation and indirect request to see GM technologies developed and marketed. Specifically, they argue that before a technology should be regulated for possible risks, those risks must be demonstrated as scientifically solid and quantifiable.\r\nAlthough the definition of â€Å"sound science” is itself controversial, proponents cite that regulatory agencies such as the EPA and FDA have been too quick to regulate technologies without frank inductionâ€arguing that such government interference not only creates fiscal disincentives for technological innovation nevertheless in truth causes social abuse by dela ying or preventing important technologies from becoming available. Such a perspective views government regulation as a risk in itself.\r\nBy contrast, advocates of the precautionary principle stress the macrocosm of scientific un acceptedties associated with many modern environmental and health issues. They have proposed a fabric for decision making that slip ones minds on the side of precaution (â€Å"better safe than lamentable”). Major components include the following: (1) look harm and prevent it; (2) place the saddle of proof on polluters to provide evince of sentry duty, not on society to try harm; (3) always examine ersatz solutions; and (4) include affected parties in parliamentary governance of technologies.\r\nCritics argue that the precautionary principle is little more than a scientific disguise for anti-technology politics (187). Testing of GMOs in our food products should be done in a similar way as drugs are tested. The way that it stands now, all co nsumers are being treated as ginzo pigs with this technology, and some are not convinced that it’s not having an impact on the health of consumers. The CDC has reported an 18 percent increase in food allergies among children on a lower floor the age of 18 from 1997 to 2007.\r\nEven though there have been no grand term scientific studies conducted to measure the health impacts of ingesting GMOs, some proponents use the absence of evidence as proof that GMOs are safe, but critics counter that absence of evidence cannot aid as GMOs safety, and accuse biotechnology corporations and governments of conducting an ungoverned experimentation by allowing GMOs into the human diet (192).\r\nAs of 2010 no scientific studies have shown conclusively that currently licensed GMO foods harm human health. However, in many cases there is continued concern that the data and studies living GMO use are insufficient to adjudge GMO use safe, especially with regard to use in the open environm ent and over successive generations (419).\r\nIn the United States, as mentioned early, manufacturers are only required to label genetically modified foods if the food has a significantly different nutritional property, or unexpected allergens, or if the food contains toxins that are higher than acceptable levels, whereas organically grown foods to which they would be labeled is considered a automatic or optional label by the FDA and USDA, and have a more stringent set of labeling requirements that producers of these products must adhere to.\r\nâ€Å"The carriage of genetically modified substances above certain very low thresholds disqualifies the organic label. extreme farmers therefore sustained economic losings because of transgenic contamination of their crops” (186). aliment label regulations in the United States are meant to tell consumers the ingredients, and nutritional composition of packaged food for sale. The affair of food labels, are to allow consumers to d ress an informed decision on whether or not to purchase a position product.\r\nThere are polls in the United States that show roughly 85 percent of Americans want food labeling for products containing GMOs, in so far government officials are resistant to mandating GMO labeling of food products stemming from pressure by the proponents of GMO production. The health and safety of this nation is at risk of being one huge nationwide experiment with genetically engineered foods, and if the biotech corporations and scientists are wrong active the safety of these products, it may have irretrievable consequences not only in the United States, but across the entire world.\r\nIt would be prudent for the government entities that were created to protect consumers, to err on the side of caution earlier than on the side corporations. Americans have the right to know what is in the food products that we are purchasing, and the confidence in government agencies that are overseeing the developme nt and manufacturing of these products, that they are 100 percent safe for us to eat rightful(prenominal) as those same agencies regulate the biotech corporations that develop and introduce new drugs to the market.\r\nWorks Cited Collin, Robert William. â€Å"Genetically Modified Food. ” Environment. Westport, CT: Greenwood Press, 2008. 253-257. Battleground. Gale Virtual recognition Library. Web. 31 July 2011. Davidson, Tish. â€Å"Food Labeling. ” The Gale Encyclopedia of Diets: A Guide to Health and Nutrition. Ed. Jacqueline L. Longe. Vol. 1. Detroit: Gale, 2008. 407-412. Gale Virtual filename extension Library. Web. 31 July 2011. McIntosh, Philip. â€Å"Genetically Modified Organisms (GMO).\r\n” Food: In Context. Ed. Brenda Wilmoth Lerner and K. Lee Lerner. Vol. 1: publicize Food to International Fund for hoidenish Development. Detroit: Gale, 2011. 416-421. Gale Virtual Reference Library. Web. 9 Aug. 2011. Restivo, Sal and shaft H. Denton. â€Å"Genet ically Modified Organisms. ” Science and Technology. Ed. Vol. 1. Westport, CT: Greenwood Press, 2008. 182-195. Battleground. Gale Virtual Reference Library. Web. 31 July 2011.\r\n'

'An Analysis of Frida Kahlo and Carmen Lomas Garza Essay\r'

'Cultural Versus Opportunities: An Analysis of Frida Kahlo And Carmen Lomas Garza haggle 1,715 Both of these pictures show the love and desire to practice on to nonp areils heritage and family traditions which is extremely important in Hispanic families. Both with vivid colors and images. In Kahlo’s â€Å" egotism Portrait on the rim Line amongst Mexico and the unite States”, even though she is a Mexi send packing woman living in a non-Mexi feces country, she is able to accept both sides and uphold on to her avow Mexi stop heritage and subtlety which it seems she preferred.\r\nIn Garza’s â€Å" camas Para Suenos”(Beds for Dreams), Garza is showing the love and closeness she had with her babe and how her beat allowed them to daydream and reach after those dreams as they kept in touch with their heritage and culture which is evident in her work. Holding on to ones own culture is important. It should non be forgotten. It should be embraced and tought to ones own children. As Kahlo’s word-painting depicts, learning of others heritage and culture can be another way of embracing your own and learning to appreciate and discover it all over. The vent of culture can be devastating to the identity element of nations and families.\r\nBrief facts ab forbidden artist Frida Kahlo’s childhood and adult years introduce her complex disembodied spirit of the mind and spirit. Frida. ( Dec 4, 2002) The Christian Century from delightful Arts and Music Collection via Gale) The artwork evokes magical realism without attempting to imitate the gifted Mexican artist, who multicolored â€Å"what she sees in her heart, on top of what she sees with her eyes. ” Kahlo’s Self Portrait on the Border Line Between Mexico and the join States, painted in 1932, is a precise(prenominal) revealing work that gives a glimpse into the heart, mind, and nous of Kahlo herself.\r\nThe painting speaks of the connection, or the lack on that pointof, between Mexico and the united States. It is a rattling subtle, yet amazingly sizable painting. Kahlo did this painting while she waited for her husband, Diego Rivera, to finish painting his wall painting in Detroit. During this time she suffered a traumatic spontaneous abortion and was admitted to the Henry Ford hospital. She felt very solitary(a) and isolated from life and all that she knew. This painting is an conceptualisation of how Kahlo viewed herself stuck somewhere in limbo, in a seat far away from her beloved Mexican homeland. P 34(1) In the front, at the render, of each side of the painting lies root.\r\nOn the side that is connected with the get together States the root are actually cables or corduroys that get by from some industrial object. The roots of these objects are stark and take different shapes such as farseeing and reaching or curled. They are clear standardised industrial cords and are not needs reflective of boththing that is natural. On the other side, the Mexican side, the roots are actual roots of engrafts that grow out like natural roots, reaching into the ground. What makes these roots significant, parenthesis from their self-explanatory differences, lies in the fact that one of the cords reaches down, and under Kahlo, touching the roots of another plant.\r\nThat plant appears to have brown pods which could easily represent how the industrial unnatural reality of the United States is smothering and cleanup spot all that is natural, and in this case Mexico as well. It is distri exclusivelyive and dark in nature. This is further emphasized by the fact that Mexico’s roots are very natural and organic, whereas the United States’ roots are dark, and intelligibly manmade and unnatural. In this painting, show Kahlo wearing an decorate that is very reminiscent of an American trim. It is a simple cause hardly it is pink and has many ruffles along the bottom of the skirt.\r\nI n some ways it seems reflective of the civilized War era, without the presence of a powerful gang skirt underneath, or perhaps a dress of the old West days in the United States. Whatever the case it is not a dress that is reflective of Kahlo but of the United States . In addition, in the hand that is facing towards Mexico Kahlo holds a Mexican flag. In the hand that is facing towards the United States she holds a cigarette. Her hold are crossed. This all suggests influences she likes, dislikes, and is perhaps confused by.\r\nShe is, in this picture, part of both worlds and clearly the side that is comparative to Mexico is patriotic and very Mexican in spirit. moreover the hand that holds a cigarette clearly speaks of the industrial and damaging nature of the United States, perhaps suggesting the negatively charged influence the United States has on Mexico. As it pertains to unearthly icons or images there are no obvious religious images on the side with the United States. How ever, when one asks that question, regarding religious, one may well argue that industrialization, manufacturing, and smokestacks, is the piety of the United States.\r\nOn the Mexican side are many references to the history and the religion of Mexico. There is what appears to be a goddess statue with two infants, a statue from old-fashioned Aztec religions perhaps, and the ancient architectural elements of Mexico. The entire natural presentation of Mexico is offered in a religious nature, even incorporating a skull which could well relate to the Day of the Dead, a religious spend for Mexico. The religion of the United States, in this case, would be visual modality production, destruction of the earth, and money.\r\nThe fact that Kahlo is in the center of the painting does not suggest any common ground, but rather speaks, it would seem, of some internal struggle inside Kahlo as she sees her nation influenced and perhaps destroyed by the United States. She is clearly a part of the United States and if one looks at her life one can see that her involvement with Diego clearly put her in close relationship with the dealings of the United States. But, she is clearly sending an image that indicates she is not happy with the United States and finds far more peace and beauty in Mexico, her home.\r\nSchjeldahl, P. (Nov 5, 2007) Kahlo is authentically a national treasure of Mexico, a country that her work expresses not merely as a culture but as a complete civilization, with profound roots in some(prenominal) pasts and with proper styles of modernity. P (92) In Carmen Lomas Garzas painting â€Å"Camas Para Suenos” (Beds for Dreams), two children can be spotted, seated on the detonator of their home, gazing up at the skilful moon. Beneath them in the fareroom, their mother is making the bed ready for the children to sleep in, and a crucifix can be seen hanging on the wall nates her.\r\nThis image recalls a time of simplicity, where children can peacefully sit and star gaze, while their apron-wearing mothers make the beds in which they will sleep in. The image is portrayed by the scope of a child, and its message calls for Mexicans to remember their culture. Roback, D. (July 13, 1990). In the midst of racism and discrimination, Garza tries not to draw upon any of that; instead, she looks to the family for resolution Mexican-American Garza has generously afforded readers a glimpse of her hold dear childhood in a poor countryfied Hispanic community.\r\nHer daily activities and fond memories are related to in paintings . Of the painting Garza stated â€Å"My sister and I used to go up on the roof on summer nights and just stay there and talk about the stars and the constellations. We also talked about the future. I knew since I was 13 years old that I wanted to be an artist. And all those things that I imagine of doing as an artist, I’m finally doing now. My mother was the one who inspired me to be an artist. She made up ou r beds to sleep in and have regular dreams, but she also laid out the bed for our dreams of the future. P 54(2) This painting was inspired by youthful conversations with her sister and their desire to become artists and focuses on the joyful memories of frequent life with her family. The two sisters, Garza being one, are sit on the roof close to the moon and stars, manduction their dreams with on another. The fact that they were Mexicans, in the United States did not change the fact that they had dreams they wished to accomplish.\r\n'

'Bayesian Inference\r'

'Biostatistics (2010), 11, 3, pp. 397â€412 inside:10. 1093/biostatistics/kxp053 Advance Access publication on declination 4, 2009 Bayesian induction for generalised bi delimitatear conflate deterrent examples YOUYI FONG Downloaded from http://biostatistics. oxfordjournals. org/ at Cornell University library on April 20, 2013 Department of Biostatistics, University of Washington, Seattle, WA 98112, USA ? HAVARD RUE Department of Mathematical Sciences, The Norwegian University for Science and Techno recordy, N-7491 Trondheim, Norway JON WAKEFIELD? Departments of Statistics and Biostatistics, University of Washington, Seattle, WA 98112, USA [email protected] ashington. edu S UMMARY generalised analog intricate baffles (GLMMs) continue to work in popularity payable to their ability to directly recognise multiple levels of dependency and sit down distinguishable selective information types. For sm every(prenominal) sample sizes especially, likeliness- base infer ence whoremaster be unreliable with variance parts universe particularly vexed to estimate. A Bayesian ascend is appealing hardly has been hampered by the lack of a fast instruction execution, and the bar in thinking anterior distri thations with variance components again being particularly problematic.Here, we briefly survey previous approaches to numeration in Bayesian employations of GLMMs and illust pass judgment in detail, the in bind of integrated nested Laplace neighborhoods in this context. We get a line a military bring on of examples, c arfully de marchesinal conditionineing anterior(prenominal) distri stillions on meaningful quantities in each case. The examples c everywhither a wide flap of selective information types including those requiring smoothing everywhere time and a comparatively complicated slat regulate for which we examine our preliminary specification in terms of the imp resided degrees of independence.We conclude that Bayesian inference is now unimaginatively feasible for GLMMs and provides an win several(prenominal)(prenominal) alternative to likeliness- base approaches such as penalized quasi-likelihood. As with likelihood-based approaches, great c ar is need in the analysis of assemble binary entropy since likeness strategies whitethorn be less accurate for such selective information. Keywords: Integrated nested Laplace musical themes; longitudinal data; Penalized quasi-likelihood; Prior specification; Spline models. 1.I NTRODUCTION generalised elongate interracial models (GLMMs) combine a extrapolate linear model with customary haphazard achievementuate on the linear predictor shield, to retrovert a rich family of models that ingest been utilize in a wide innovation of applications ( retrieve, e. g. Diggle and others, 2002; Verbeke and Molenberghs, 2000, 2005; McCulloch and others, 2008). This flexibility comes at a price, however, in terms of analytical tractability, which has a ? To whom residue should be addressed. c The Author 2009. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals. [email protected] rg. 398 Y. F ONG AND OTHERS outlet of implications including computingal complexness, and an unknown degree to which inference is dependent on modeling assumptions. Likelihood-based inference whitethorn be carried out coitusly slowly inwardly legion(predicate) softwargon plat radiation diagrams (except perhaps for binary solutions), still inference is dependent on asymptotic sample distri exactlyion distributions of estimators, with few guidelines available as to when such opening exit produce accurate inference. A Bayesian approach is attractive, but requires the specification of front distributions which is non straight, in particular for variance components.Computation is as rise an issue since the usual implementation is via Markov chain four-card monte Carlo (MCMC), which carri es a salient computational overhead. The seminal article of Breslow and Clayton (1993) helped to pass around GLMMs and placed an emphasis on likelihood-based inference via penalized quasi-likelihood (PQL). It is the heading of this article to describe, through a series of examples (including all of those estimateed in Breslow and Clayton, 1993), how Bayesian inference whitethorn be per stocked with computation via a fast implementation and with instruction on anterior specification. The structure of this article is as follows.In constituent 2, we define nonation for the GLMM, and in region 3, we describe the integrated nested Laplace approximation (INLA) that has recently been proposed as a computationally at rest alternative to MCMC. dent 4 gives a get of prescriptions for front specification. trio examples atomic derive 18 considered in dent 5 (with special examples being reported in the supplementary stuff and nonsense available at Biostatistics online, along with a assumption necessitate that reports the put to deathance of INLA in the binary chemical reaction situation). We conclude the paper with a contendion in sectionalisation 6. 2.T HE G ENERALIZED LINEAR coalesce MODEL GLMMs extend the generalized linear model, as proposed by Nelder and Wedderburn (1972) and comprehensively depict in McCullagh and Nelder (1989), by adding unremarkably distributed hit-or-miss do on the linear predictor outdo. Suppose Yi j is of exponential function family form: Yi j |? i j , ? 1 ? p(•), where p(•) is a member of the exponential family, that is, p(yi j |? i j , ? 1 ) = exp yi j ? i j ? b(? i j ) + c(yi j , ? 1 ) , a(? 1 ) Downloaded from http://biostatistics. oxfordjournals. org/ at Cornell University Library on April 20, 2013 for i = 1, . . . , m units (clusters) and j = 1, . . , n i , measurements per unit and where ? i j is the (scalar) ? dirty dogonical line. permit ? i j = E[Yi j |? , b i , ? 1 ] = b (? i j ) with g( ? i j ) = ? i j = x i j ? + z i j b i , where g(•) is a decreasing monotonic â€Å" merge” function, x i j is 1 ? p, and z i j is 1 ? q, with ? a p ? 1 sender of firm ? Q personal make and b i a q ? 1 transmitter of random cases, hence ? i j = ? i j (? , b i ). Assume b i |Q ? N (0, Q ? 1 ), where ? the precision hyaloplasm Q = Q (? 2 ) depends on parameters ? 2 . For some picks of model, the ground substance Q is singular; examples include random walk models (as considered in Section 5. ) and intrinsic qualified ? autoregressive models. We further abide that ? is assigned a normal introductory distribution. allow ? = (? , b ) denote the G ? 1 vector of parameters assigned Gaussian earliers. We also require earliers for ? 1 (if not a constant) and for ? 2 . Let ? = (? 1 , ? 2 ) be the variance components for which non-Gaussian antecedents atomic number 18 ? assigned, with V = dim(? ). 3. I NTEGRATED NESTED L APLACE APPROXIMATION Before the MCMC revol ution, in that respect were few examples of the applications of Bayesian GLMMs since, outside of the linear sundry(a) model, the models be analytically intractable.Kass and Steffey (1989) describe the lend oneself of Laplace approximations in Bayesian hierarchic models, while Skene and Wakefield Bayesian GLMMs 399 (1990) engrossd quantitative integrating in the context of a binary GLMM. The example of MCMC for GLMMs is particularly appealing since the conditional independencies of the model whitethorn be secondhand when the required conditional distributions ar calculated. Zeger and Karim (1991) exposit approximate Gibbs leave for GLMMs, with nonstandard conditional distributions being approximated by normal distributions.More general Metropolisâ€Hastings algorithms atomic number 18 straightforward to nominate (see, e. g. Clayton, 1996; Gamerman, 1997). The winBUGS (Spiegelhalter, Thomas, and Best, 1998) parcel example manuals contain many an(prenominal) GLMM examples. in that location are now a variety of additional software platforms for fitting GLMMs via MCMC including JAGS (Plummer, 2009) and BayesX (Fahrmeir and others, 2004). A large practical impediment to data analysis exploitation MCMC is the large computational burden. For this reason, we now briefly review the INLA computational approach upon which we revolve about.The method combines Laplace approximations and numerical integration in a very efficient air (see Rue and others, 2009, for a much extensive sermon). For the GLMM described in Section 2, the shtup is given by m Downloaded from http://biostatistics. oxfordjournals. org/ at Cornell University Library on April 20, 2013 ? y ? ? ? ?(? , ? |y ) ? ?(? |? )? (? ) i=1 y ? p(y i |? , ? ) m i=1 1 ? ? Q ? ? b ? ?(? )? (? )|Q (? 2 )|1/2 exp ? b T Q (? 2 )b + 2 y ? log p(y i |? , ? 1 ) , where y i = (yi1 , . . . , yin i ) is the vector of observations on unit/cluster i.We wish to pick up the keister y y bare(a)s ? (? g |y ), g = 1, . . . , G, and ? (? v |y ), v = 1, . . . , V . The number of variance components, V , should not be too large for accurate inference (since these components are integrated out via Cartesian product numerical integration, which does not scale well with dimension). We write y ? (? g |y ) = which may be evaluated via the approximation y ? (? g |y ) = K ? ? y ? ?(? g |? , y ) ? ?(? |y )d? , ? ? y ? ?(? g |? , y ) ? ? (? |y )d? ? y ? ? (? g |? k , y ) ? ? (? k |y ) ? k, ? (3. 1) k=1 here Laplace (or other related analytical approximations) are applied to carry out the integrations required ? ? for paygrade of ? (? g |? , y ). To produce the grid of points {? k , k = 1, . . . , K } over which numerical inte? y gration is performed, the mode of ? (? |y ) is located, and the Hessian is approximated, from which the grid is created and exploited in (3. 1). The output of INLA consists of posterior marginal distributions, which can be summarized via means, variances, and quantile s. Importantly for model comparison, the normaly izing constant p(y ) is calculated.The evaluation of this measuring stick is not straightforward apply MCMC (DiCiccio and others, 1997; Meng and Wong, 1996). The distortion information criterion (Spiegelhalter, Best, and others, 1998) is popular as a model selection tool, but in random-effects models, the unuttered approximation in its hire is valid still when the trenchant number of parameters is much smaller than the number of independent observations (see Plummer, 2008). 400 Y. F ONG AND OTHERS 4. P RIOR DISTRIBUTIONS 4. 1 Fixed effects Recall that we strike ? is normally distributed. Often there leave alone be adapted information in the data for ? o be well estimated with a normal prior with a large variance (of course there entrust be circumstances under(a) which we would like to plant more informative priors, e. g. when there are many correlated covariates). The map of an im prim prior for ? allow for often get g oing to a ripe posterior though care should be taken. For example, Wakefield (2007) shows that a Poisson likelihood with a linear link can lead to an improper posterior if an improper prior is exercised. Hobert and Casella (1996) discuss the use up of improper priors in linear assorted effects models.If we wish to use informative priors, we may specify independent normal priors with the parameters for each component being sticked via specification of 2 quantiles with associated probabilities. For logistic and log-linear models, these quantiles may be given on the exponentiated scale since these are more interpretable (as the betting odds ratio and rate ratio, personly). If ? 1 and ? 2 are the quantiles on the exponentiated scale and p1 and p2 are the associated probabilities, wherefore the parameters of the normal prior are given by ? = ? = z 2 log(? 1 ) ? z 1 log(? 2 ) , z2 ? 1 Downloaded from http://biostatistics. oxfordjournals. org/ at Cornell University Library on April 20, 2013 log(? 2 ) ? log(? 1 ) , z2 ? z1 where z 1 and z 2 are the p1 and p2 quantiles of a standard normal random variable. For example, in an epidemiologic context, we may wish to specify a prior on a copulation risk parameter, exp(? 1 ), which has a median of 1 and a 95% point of 3 (if we think it is unlikely that the relative risk associated with a unit improver in exposure exceeds 3). These specifications lead to ? 1 ? N (0, 0. 6682 ). 4. 2 Variance componentsWe begin by describing an approach for choosing a prior for a single random effect, based on Wakefield (2009). The basic idea is to specify a range for the more interpretable marginal distribution of bi and use this to drive specification of prior parameters. We state a trivial lemma upon which prior specification is based, but original define some notation. We write ? ? Ga(a1 , a2 ) for the da Gamma distribution with un? normalized minginess ? a1 ? 1 exp(? a2 ? ). For q-dimensional x , we write x ? Tq (? , , d) for t he scholar’s x x t distribution with unnormalized immersion [1 + (x ? ? )T ? 1 (x ? )/d]? (d+q)/2 . This distribution has military position ? , scale hyaloplasm , and degrees of immunity d. L EMMA 1 Let b|? ? N (0, ? ?1 ) and ? ? Ga(a1 , a2 ). Integration over ? gives the marginal distribution of b as T1 (0, a2 /a1 , 2a1 ). To decide upon a prior, we give a range for a generic random effect b and specify the degrees of freev d dom, d, and then solve for a1 and a2 . For the range (? R, R), we use the relationship ±t1? (1? q)/2 a2 /a1 = d ±R, where tq is the carbon ? qth quantile of a Student t random variable with d degrees of emancipation, to give d a1 = d/2 and a2 = R 2 d/2(t1? (1? q)/2 )2 .In the linear mixed effects model, b is directly interpretable, while for binomial or Poisson models, it is more appropriate to think in terms of the marginal distribution of exp(b), the residual odds and rate ratio, respectively, and this distribution is log Studentâ€℠¢s t. For example, if we choose d = 1 (to give a Cauchy marginal) and a 95% range of [0. 1, 10], we take R = log 10 and obtain a = 0. 5 and b = 0. 0164. Bayesian GLMMs 401 ?1 Another convenient choice is d = 2 to give the exponential distribution with mean a2 for ? ?2 . This leads to closed-form expressions for the more interpretable quantiles of ? o that, for example, if we 2 specify the median for ? as ? m , we obtain a2 = ? m log 2. Unfortunately, the use of Ga( , ) priors has become popular as a prior for ? ?2 in a GLMM context, arising from their use in the winBUGS examples manual. As has been pointed out many times (e. g. Kelsall and Wakefield, 1999; Gelman, 2006; Crainiceanu and others, 2008), this choice places the majority of the prior mass away from nix and leads to a marginal prior for the random effects which is Student’s t with 2 degrees of exemption (so that the tails are much heavier than even a Cauchy) and difficult to justify in any practical setting.We now specify another trivial lemma, but first establish notation for the Wishart distribution. For the q ? q nonsingular ground substance z , we write z ? Wishartq (r, S ) for the Wishart distribution with unnormalized Downloaded from http://biostatistics. oxfordjournals. org/ at Cornell University Library on April 20, 2013 Q Lemma: Let b = (b1 , . . . , bq ), with b |Q ? iid Nq (0, Q ? 1 ), Q ? Wishartq (r, S ). Integration over Q b as Tq (0, [(r ? q + 1)S ]? 1 , r ? q + 1). S gives the marginal distribution of The margins of a multivariate Student’s t are t also, which allows r and S to be chosen as in the univariate case.Specifically, the kth element of a generic random effect, bk , follows a univariate Student t distribution with location 0, scale S kk /(r ? q + 1), and degrees of freedom d = r ? q + 1, where S kk d is element (k, k) of the inverse of S . We obtain r = d + q ? 1 and S kk = (t1? (1? q)/2 )2 /(d R 2 ). If a priori b are correlated we may specify S jk = 0 for j = k and we have no reason to intrust that elements of S kk = 1/Skk , to restore the univariate specification, recognizing that with q = 1, the univariate Wishart has parameters a1 = r/2 and a2 = 1/(2S).If we believe that elements of b are dependent then we may specify the correlations and solve for the off-diagonal elements of S . To ensure propriety of the posterior, proper priors are required for ; Zeger and Karim (1991) use an improper prior for , so that the posterior is improper also. 4. 3 trenchant degrees of freedom variance components prior z z z z density |z |(r ? q? 1)/2 exp ? 1 tr(z S ? 1 ) . This distribution has E[z ] = r S and E[z ? 1 ] = S ? 1 /(r ? q ? 1), 2 and we require r > q ? 1 for a proper distribution.In Section 5. 3, we describe the GLMM trifleation of a slat model. A generic linear slat model is given by K yi = x i ? + k=1 z ik bk + i , where x i is a p ? 1 vector of covariates with p ? 1 associated stiff effects ? , z ik denote the spline 2 basis , bk ? iid N (0, ? b ), and i ? iid N (0, ? 2 ), with bk and i independent. Specification of a prior for 2 is not straightforward, but may be of great importance since it contributes to determining the amount ? b of smoothing that is applied. Ruppert and others (2003, p. 77) raise concerns, â€Å"about the instability of automatic smoothing parameter selection even for single predictor models”, and continue, â€Å"Although we are attracted by the automatic nature of the mixed model-REML approach to fitting bilinear models, we discour ripen blind credence of whatever answer it provides and recommend looking at other amounts of smoothing”. While we would echo this general advice, we believe that a Bayesian mixed model approach, with conservatively chosen priors, can increase the stability of the mixed model representation. at that place has been 2 some raillery of choice of prior for ? in a spline context (Crainiceanu and others, 2005, 2008). More general discussion can be institute in Natarajan and Kass (2000) and Gelman (2006). In practice (e. g. Hastie and Tibshirani, 1990), smoothers are often applied with a bushel degrees of freedom. We extend this rationale by examining the prior degrees of freedom that is implied by the choice 402 Y. F ONG AND OTHERS ?2 ? b ? Ga(a1 , a2 ). For the general linear mixed model y = x ? + zb + , we have x z where C = [x |z ] is n ? ( p + K ) and C y = x ? + z b = C (C T C + 0 p? p 0K ? p )? 1 C T y , = 0 p? K 2 cov(b )? 1 b ? )? 1 C T C }, Downloaded from http://biostatistics. xfordjournals. org/ at Cornell University Library on April 20, 2013 (see, e. g. Ruppert and others, 2003, Section 8. 3). The integrality degrees of freedom associated with the model is C df = tr{(C T C + which may be decomposed into the degrees of freedom associated with ? and b , and extends easily to situations in which we have additional random effects, beyond those associated with the spline basis (such an example is considered in Section 5. 3). In each of these situations, the degrees of freedom associated C with the respective parameter is obtained by summing the appropriate diagonal elements of (C T C + )? C T C . Specifically, if we have j = 1, . . . , d sets of random-effect parameters (there are d = 2 in the model considered in Section 5. 3) then let E j be the ( p + K ) ? ( p + K ) diagonal matrix with ones in the diagonal positions identical to set j. wherefore the degrees of freedom associated with this set is E C df j = tr{E j (C T C + )? 1 C T C . Note that the powerful degrees of freedom changes as a function of K , as expected. To evaluate , ? 2 is required. If we specify a proper prior for ? 2 , then we may specify the 2 2 joint prior as ? (? b , ? 2 ) = ? (? 2 )? (? b |? 2 ).Often, however, we gull the improper prior ? (? 2 ) ? 1/? 2 since the data provide equal information with respect to ? 2 . Hence, we have ready the substitution of an estimate for ? 2 (for example, from the fitting of a spline model in a likelihood implementation) to be a practically reasonable strategy. As a simple nonspline demonstration of the derived effective degrees of freedom, consider a 1-way analysis of variance model Yi j = ? 0 + bi + i j 2 with bi ? iid N (0, ? b ), i j ? iid N (0, ? 2 ) for i = 1, . . . , m = 10 radicals and j = 1, . . . , n = 5 observa? 2 tions per group. For illustration, we assume ? ? Ga(0. 5, 0. 005). Figure 1 displays the prior distribution for ? , the implied prior distribution on the effective degrees of freedom, and the bivariate darn of these quantities. For clarity of plotting, we exclude a small number of points beyond ? > 2. 5 (4% of points). In beautify (c), we have placed dashed horizontal lines at effective degrees of freedom equal to 1 (complete smoothing) and 10 (no smoothing). From panel (b), we conclude that here the prior choice favors preferably strong smoothing. This may be contrasted with the gamma prior with parameters (0. 001, 0. 001 ), which, in this example, gives reater than 99% of the prior mass on an effective degrees of freedom greater than 9. 9, again showing the inappropriateness of this prior. It is appealing to extend the above seam to nonlinear models but unfortunately this is not straightforward. For a nonlinear model, the degrees of freedom may be approximated by C df = tr{(C T W C + where W = diag Vi? 1 d? i dh 2 )? 1 C T W C }, and h = g ? 1 denotes the inverse link function. Unfortunately, this quantity depends on ? and b , which means that in practice, we would have to use prior estimates for all of the parameters, which may not be practically possible.Fitting the model exploitation likelihood and then substituting in estimates for ? and b seems philosophically dubious. Bayesian GLMMs 403 Downloaded from http://biostatistics. oxfordjournals. org/ at Cornell University Library on April 20, 2013 Fig. 1. Gamma prior for ? ?2 with parameters 0. 5 and 0. 005, (a) implied prior for ? , (b) implied prior for the effective degrees of freedom, and (c) effective degrees of freedom versus ? . 4. 4 Random walk models Conditionally represented smoothing models are popular for random effects in both(prenominal) lay and spatial applications (see, e. g. Besag and others, 1995; Rue and Held, 2005).For illustration, consider models of the form ? (m? r ) Q u 2 exp ? p(u |? u ) = (2? )? (m? r )/2 |Q |1/2 ? u 1 T u Qu , 2 2? u (4. 1) 404 Y. F ONG AND OTHERS where u = (u 1 , . . . , u m ) is the collection of random effects, Q is a (scaled) â€Å"precision” matrix of rank Q m ? r , whose form is situated by the application at hand, and |Q | is a generalized determinant which is the product over the m ? r nonzero eigenvalues of Q . Picking a prior for ? u is not straightforward because ? u has an interpretation as the conditional standard deviation, where the elements that are conditioned upon depends on the application.We may simulate realizations from (4. 1) to examine candidate p rior distributions. overdue to the rank deficiency, (4. 1) does not define a hazard density, and so we cannot directly simulate from this prior. However, Rue and Held (2005) give an algorithm for generating samples from (4. 1): 1. Simulate z j ? N (0, ?? 1 ), for j = m ? r + 1, . . . , m, where ? j are the eigenvalues of Q (there are j m ? r nonzero eigenvalues as Q has rank m ? r ). 2. decrease u = z m? r +1 e n? r +1 + z 3 e 3 + • • • + z n e m = E z , where e j are the corresponding eigenvectors of Q , E is the m ? (m ? ) matrix with these eigenvectors as columns, and z is the (m ? r ) ? 1 vector containing z j , j = m ? r + 1, . . . , m. The simulation algorithm is conditioned so that samples are zero in the null-space of Q ; if u is a sample and the null-space is spanned by v 1 and v 2 , then u T v 1 = u T v 2 = 0. For example, suppose Q 1 = 0 so that the null-space is spanned by 1, and the rank deficiency is 1. Then Q is improper since the eigenvalue corre sponding to 1 is zero, and samples u produced by the algorithm are such that u T 1 = 0. In Section 5. 2, we use this algorithm to evaluate opposite priors via simulation.It is also useful to note that if we wish to cast the marginal variances only, simulation is not required, as they are available as the diagonal elements of the matrix j ?? 1 e j e T . j j 5. E XAMPLES Here, we report 3 examples, with 4 others described in the supplementary material available at Biostatistics online. Together these cover all the examples in Breslow and Clayton (1993), along with an additional spline example. In the first example, results exploitation the INLA numerical/analytical approximation described in Section 3 were compared with MCMC as implemented in the JAGS software (Plummer, 2009) and found to be accurate.For the models considered in the second and third examples, the approximation was compared with the MCMC implementation contained in the INLA software. 5. 1 longitudinal data We consi der the much analyzed epilepsy data set of Thall and Vail (1990). These data concern the number ? of seizures, Yi j for patient i on catch j, with Yi j |? , b i ? ind Poisson(? i j ), i = 1, . . . , 59, j = 1, . . . , 4. We concentrate on the 3 random-effects models fitted by Breslow and Clayton (1993): log ? i j = x i j ? + b1i , (5. 1) (5. 2) (5. 3) Downloaded from http://biostatistics. oxfordjournals. rg/ at Cornell University Library on April 20, 2013 log ? i j = x i j ? + b1i + b2i V j /10, log ? i j = x i j ? + b1i + b0i j , where x i j is a 1 ? 6 vector containing a 1 (representing the intercept), an indicator for baseline measurement, a treatment indicator, the baseline by treatment interaction, which is the parameter of interest, age, and all an indicator of the fourth visit (models (5. 1) and (5. 2) and denoted V4 ) or visit number coded ? 3, ? 1, +1, +3 (model (5. 3) and denoted V j /10) and ? is the associated fixed effect. All 3 models 2 include patient-specific rand om effects b1i ? N 0, ? , while in model (5. 2), we introduce independent 2 ). warning (5. 3) includes random effects on the slope associated with â€Å"measurement errors,” b0i j ? N (0, ? 0 Bayesian GLMMs 405 Table 1. PQL and INLA summaries for the epilepsy data Variable Base Trt Base ? Trt Age V4 or V/10 ? 0 ? 1 ? 2 Model (5. 1) PQL 0. 87 ± 0. 14 ? 0. 91 ± 0. 41 0. 33 ± 0. 21 0. 47 ± 0. 36 ? 0. 16 ± 0. 05 †0. 53 ± 0. 06 †INLA 0. 88 ± 0. 15 ? 0. 94 ± 0. 44 0. 34 ± 0. 22 0. 47 ± 0. 38 ? 0. 16 ± 0. 05 †0. 56 ± 0. 08 †Model (5. 2) PQL 0. 86 ± 0. 13 ? 0. 93 ± 0. 40 0. 34 ± 0. 21 0. 47 ± 0. 35 ? 0. 10 ± 0. 09 0. 36 ± 0. 04 0. 48 ± 0. 06 †INLA 0. 8 ± 0. 15 ? 0. 96 ± 0. 44 0. 35 ± 0. 23 0. 48 ± 0. 39 ? 0. 10 ± 0. 09 0. 41 ± 0. 04 0. 53 ± 0. 07 †Model (5. 3) PQL 0. 87 ± 0. 14 ? 0. 91 ± 0. 41 0. 33 ± 0. 21 0. 46 ± 0. 36 ? 0. 26 ± 0. 16 †0. 52 ± 0. 06 0. 74 ± 0. 16 INLA 0. 88 ± 0. 14 ? 0. 94 ± 0. 44 0. 34 ± 0. 22 0. 47 ± 0. 38 ? 0. 27 ± 0. 16 †0. 56 ± 0. 06 0. 70 ± 0. 14 Downloaded from http://biostatistics. oxfordjournals. org/ at Cornell University Library on April 20, 2013 visit, b2i with b1i b2i ? N (0, Q ? 1 ). (5. 4) We assume Q ? Wishart(r, S ) with S = S11 S12 . For prior specification, we begin with the bivariate S21 S22 model and assume that S is diagonal.We assume the upper 95% point of the priors for exp(b1i ) and exp(b2i ) are 5 and 4, respectively, and that the marginal distributions are t with 4 degrees of freedom. Following the procedure outlined in Section 4. 2, we obtain r = 5 and S = diag(0. 439, 0. 591). We take ? 2 the prior for ? 1 in model (5. 1) to be Ga(a1 , a2 ) with a1 = (r ? 1)/2 = 2 and a2 = 1/2S11 = 1. cxl (so that this prior coincides with the marginal prior obtained from the bivariate specification). In model (5. 2), ? 2 ? 2 we assume b1i and b0i j are independent, and t hat ? 0 follows the similar prior as ? , that is, Ga(2, 1. 140). We assume a flat prior on the intercept, and assume that the rate ratios, exp(? j ), j = 1, . . . , 5, lie between 0. 1 and 10 with probability 0. 95 which gives, using the approach described in Section 4. 1, a normal prior with mean 0 and variance 1. 172 . Table 1 gives PQL and INLA summaries for models (5. 1â€5. 3). There are some differences between the PQL and Bayesian analyses, with just about larger standard deviations under the latter, which probably reflects that with m = 59 clusters, a little accuracy is alienated when using asymptotic inference.There are some differences in the point estimates which is at least partly due to the nonflat priors usedâ€the priors have relatively large variances, but here the data are not so abundant so there is sensitivity to the prior. reassuringly under all 3 models inference for the baseline-treatment interaction of interest is virtually y identical and suggests no s ignificant treatment effect. We may compare models using log p(y ): for 3 models, we obtain values of ? 674. 8, ? 638. 9, and ? 665. 5, so that the second model is strongly preferred. 5. Smoothing of support cohort effects in an age-cohort model We analyze data from Breslow and Day (1975) on breast cancer evaluate in Iceland. Let Y jk be the number of breast cancer of cases in age group j (20â€24,. . . , 80â€84) and birth cohort k (1840â€1849,. . . ,1940â€1949) with j = 1, . . . , J = 13 and k = 1, . . . , K = 11. Following Breslow and Clayton (1993), we assume Y jk |? jk ? ind Poisson(? jk ) with log ? jk = log n jk + ? j + ? k + vk + u k (5. 5) and where n jk is the person-years denominator, exp(? j ), j = 1, . . . , J , represent fixed effects for age relative risks, exp(? is the relative risk associated with a one group increase in cohort group, vk ? iid 406 Y. F ONG AND OTHERS 2 N (0, ? v ) represent unstructured random effects associated with cohort k, with smoo th cohort terms u k following a second-order random-effects model with E[u k |{u i : i < k}] = 2u k? 1 ? u k? 2 and Var(u k |{u i : 2 i < k}) = ? u . This latter model is to allow the judge to vary smoothly with cohort. An equivalent representation of this model is, for 2 < k < K ? 1, 1 E[u k |{u l : l = k}] = (4u k? 1 + 4u k+1 ? u k? 2 ? u k+2 ), 6 Var(u k |{u l : l = k}) = 2 ? . 6 Downloaded from http://biostatistics. oxfordjournals. org/ at Cornell University Library on April 20, 2013 The rank of Q in the (4. 1) representation of this model is K ? 2 reflecting that both the general level and the overall trend are aliased (hence the appearance of ? in (5. 5)). The term exp(vk ) reflects the unstructured residual relative risk and, following the argument in Section 4. 2, we specify that this quantity should lie in [0. 5, 2. 0] with probability 0. 95, with a marginal log Cauchy ? 2 distribution, to obtain the gamma prior ? v ? Ga(0. 5, 0. 00149).The term exp(u k ) refl ects the smooth component of the residual relative risk, and the specification of a 2 prior for the associated variance component ? u is more difficult, given its conditional interpretation. Using the algorithm described in Section 4. 2, we examined simulations of u for different choices of gamma ? 2 hyperparameters and decided on the choice ? u ? Ga(0. 5, 0. 001); Figure 2 shows 10 realizations from the prior. The rationale here is to examine realizations to see if they conform to our prior expectations and in particular exhibit the required amount of smoothing.All but one of the realizations vary smoothly across the 11 cohorts, as is desirable. Due to the tail of the gamma distribution, we will always have some extreme realizations. The INLA results, summarized in graphical form, are presented in Figure 2(b), on board likelihood fits in which the birth cohort effect is incorporated as a linear term and as a factor. We see that the smoothing model provides a smooth fit in birth coh ort, as we would hope. 5. 3 B-Spline nonparametric regression We demonstrate the use of INLA for nonparametric smoothing using O’Sullivan splines, which are based on a B-spline basis.We illustrate using data from Bachrach and others (1999) that concerns longitudinal measurements of spinal bone mineral density (SBMD) on 230 female subjects aged between 8 and 27, and of 1 of 4 ethnic groups: Asiatic, Black, Latino, and White. Let yi j denote the SBMD measure for subject i at occasion j, for i = 1, . . . , 230 and j = 1, . . . , n i with n i being between 1 and 4. Figure 3 shows these data, with the gray lines indicating measurements on the same woman. We assume the model K Yi j = x i ? 1 + agei j ? 2 + k=1 z i jk b1k + b2i + ij, where x i is a 1 ? vector containing an indicator for the ethnicity of individual i, with ? 1 the associated 4 ? 1 vector of fixed effects, z i jk is the kth basis associated with age, with associated parameter b1k ? 2 2 N (0, ? 1 ), and b2i ? N (0, ? 2 ) are woman-specific random effects, finally, i j ? iid N (0, ? 2 ). All random terms are faux independent. Note that the spline model is assumed common to all ethnic groups and all women, though it would be straightforward to allow a different spline for each ethnicity. Writing this model in the form y = x ? + z 1b1 + z 2b 2 + = C ? + . Bayesian GLMMs 407Downloaded from http://biostatistics. oxfordjournals. org/ at Cornell University Library on April 20, 2013 Fig. 2. (a) Ten realizations (on the relative risk scale) from the random effects second-order random walk model in which the prior on the random-effects precision is Ga(0. 5,0. 001), (b) summaries of fitted models: the solid line corresponds to a log-linear model in birth cohort, the circles to birth cohort as a factor, and â€Å"+” to the Bayesian smoothing model. we use the method described in Section 4. 3 to examine the effective number of parameters implied by the ? 2 ? 2 priors ? 1 ? Ga(a1 , a2 ) and ? 2 ? Ga( a3 , a4 ).To fit the model, we first use the R code provided in truncheon and Ormerod (2008) to construct the basis functions, which are then stimulant drug to the INLA program. Running the REML version of the model, we obtain 2 ? = 0. 033 which we use to evaluate the effective degrees of freedoms associated with priors for ? 1 and 2 . We assume the usual improper prior, ? (? 2 ) ? 1/? 2 for ? 2 . After some experimentation, we settled ? 2 408 Y. F ONG AND OTHERS Downloaded from http://biostatistics. oxfordjournals. org/ at Cornell University Library on April 20, 2013 Fig. 3. SBMD versus age by ethnicity. Measurements on the same woman are joined with gray lines.The solid curve corresponds to the fitted spline and the dashed lines to the individual fits. ?2 2 on the prior ? 1 ? Ga(0. 5, 5 ? 10? 6 ). For ? 2 , we wished to have a 90% separation for b2i of ±0. 3 which, ? 2 with 1 degree of freedom for the marginal distribution, leads to ? 2 ? Ga(0. 5, 0. 00113). Figure 4 shows t he priors for ? 1 and ? 2 , along with the implied effective degrees of freedom under the assumed priors. For the spline component, the 90% prior time interval for the effective degrees of freedom is [2. 4,10]. Table 2 compares estimates from REML and INLA implementations of the model, and we see close correspondence between the 2.Figure 4 also shows the posterior medians for ? 1 and ? 2 and for the 2 effective degrees of freedom. For the spline and random effects these correspond to 8 and 214, respectively. The latter figure shows that there is considerable variation between the 230 women here. This is confirmed in Figure 3 where we observe large vertical differences between the profiles. This figure also shows the fitted spline, which appears to mimic the trend in the data well. 5. 4 Timings For the 3 models in the longitudinal data example, INLA takes 1 to 2 s to run, using a single CPU.To get estimates with similar precision with MCMC, we ran JAGS for 100 000 iterations, which took 4 to 6 min. For the model in the temporal smoothing example, INLA takes 45 s to run, using 1 CPU. reveal of the INLA procedure can be executed in a parallel manner. If there are 2 CPUs available, as is the case with today’s dominant INTEL Core 2 Duo processors, INLA only takes 27 s to run. It is not currently possible to implement this model in JAGS. We ran the MCMC utility-grade built into the INLA software for 3. 6 million iterations, to obtain estimates of comparable accuracy, which took 15 h.For the model in the B-spline nonparametric regression example, INLA took 5 s to run, using a single CPU. We ran the MCMC utility built into the INLA software for 2. 5 million iterations to obtain estimates of comparable accuracy, the analysis taking 40 h. Bayesian GLMMs 409 Downloaded from http://biostatistics. oxfordjournals. org/ at Cornell University Library on April 20, 2013 Fig. 4. Prior summaries: (a) ? 1 , the standard deviation of the spline coefficients, (b) effecti ve degrees of freedom associated with the prior for the spline coefficients, (c) effective degrees of freedom versus ? , (d) ? 2 , the standard deviation of the between-individual random effects, (e) effective degrees of freedom associated with the individual random effects, and (f) effective degrees of freedom versus ? 2 . The vertical dashed lines on panels (a), (b), (d), and (e) correspond to the posterior medians. Table 2. REML and INLA summaries for spinal bone data. Intercept corresponds to Asian group Variable Intercept Black Hispanic White Age ? 1 ? 2 ? REML 0. 560 ± 0. 029 0. 106 ± 0. 021 0. 013 ± 0. 022 0. 026 ± 0. 022 0. 021 ± 0. 002 0. 018 0. 109 0. 033 INLA 0. 563 ± 0. 031 0. 106 ± 0. 021 0. 13 ± 0. 022 0. 026 ± 0. 022 0. 021 ± 0. 002 0. 024 ± 0. 006 0. 109 ± 0. 006 0. 033 ± 0. 002 Note: For the entries marked with a standard errors were unavailable. 410 Y. F ONG AND OTHERS 6. D ISCUSSION In this paper, we have demonstrated the use of the INLA computational method for GLMMs. We have found that the approximation strategy employed by INLA is accurate in general, but less accurate for binomial data with small denominators. The supplementary material available at Biostatistics online contains an extensive simulation study, replicating that presented in Breslow and Clayton (1993).There are some suggestions in the discussion of Rue and others (2009) on how to construct an improved Gaussian approximation that does not use the mode and the curvature at the mode. It is likely that these suggestions will improve the results for binomial data with small denominators. There is an urgent need for diagnosis tools to flag when INLA is inaccurate. Conceptually, computation for nonlinear mixed effects models (Davidian and Giltinan, 1995; Pinheiro and Bates, 2000) can also be handled by INLA but this capability is not currently available. The website www. r-inla. rg contains all the data and R scripts to perform the analyses a nd simulations reported in the paper. The latest release of software to implement INLA can also be found at this site. Recently, Breslow (2005) revisited PQL and concluded that, â€Å"PQL still performs remarkably well in comparison with more elaborate procedures in many practical situations. ” We believe that INLA provides an attractive alternative to PQL for GLMMs, and we hope that this paper stimulates the greater use of Bayesian methods for this class. Downloaded from http://biostatistics. oxfordjournals. org/ at Cornell University Library on April 20, 2013S UPPLEMENTARY MATERIAL supplemental material is available at http://biostatistics. oxfordjournals. org. ACKNOWLEDGMENT scrap of Interest: None declared. F UNDING National Institutes of wellness (R01 CA095994) to J. W. Statistics for Innovation (sfi. nr. no) to H. R. R EFERENCES BACHRACH , L. K. , H ASTIE , T. , WANG , M. C. , NARASIMHAN , B. AND M arcus , R. (1999). Bone mineral acquisition in hale Asian, Hispanic, Black and Caucasian youth. A longitudinal study. The diary of Clinical Endocrinology and Metabolism 84, 4702â€4712. B ESAG , J. , G REEN , P. J. , H IGDON , D. AND M ENGERSEN , K. 1995). Bayesian computation and stochastic systems (with discussion). statistical Science 10, 3â€66. B RESLOW, N. E. (2005). Whither PQL? In: Lin, D. and Heagerty, P. J. (editors), minutes of the Second Seattle Symposium. New York: Springer, pp. 1â€22. B RESLOW, N. E. AND C LAYTON , D. G. (1993). Approximate inference in generalized linear mixed models. ledger of the American statistical affiliation 88, 9â€25. B RESLOW, N. E. AND DAY, N. E. (1975). Indirect standardization and increasing models for rates, with reference to the age adjustment of cancer relative incidence and relative frequency data.Journal of Chronic Diseases 28, 289â€301. C LAYTON , D. G. (1996). reason out linear mixed models. In: Gilks, W. R. , Richardson, S. and Spiegelhalter, D. J. (editors), Markov Chain Monte C arlo in Practice. capital of the United Kingdom: Chapman and Hall, pp. 275â€301. Bayesian GLMMs 411 C RAINICEANU , C. M. , D IGGLE , P. J. AND ROWLINGSON , B. (2008). Bayesian analysis for penalized spline regression using winBUGS. Journal of the American statistical crosstie 102, 21â€37. C RAINICEANU , C. M. , RUPPERT, D. AND WAND , M. P. (2005). Bayesian analysis for penalized spline regression using winBUGS. Journal of statistical software 14.DAVIDIAN , M. AND G ILTINAN , D. M. (1995). Nonlinear Models for Repeated Measurement Data. capital of the United Kingdom: Chapman and Hall. D I C ICCIO , T. J. , K cigarette , R. E. , R AFTERY, A. AND WASSERMAN , L. (1997). Computing Bayes factors by combine simulation and asymptotic approximations. Journal of the American Statistical linkup 92, 903â€915. Downloaded from http://biostatistics. oxfordjournals. org/ at Cornell University Library on April 20, 2013 D IGGLE , P. , H EAGERTY, P. , L IANG , K. -Y. Oxford: Oxford Unive rsity Press. AND Z EGER , S. (2002). Analysis of Longitudinal Data, 2nd edition. FAHRMEIR , L. , K NEIB , T.AND L ANG , S. (2004). Penalized structured additive regression for space-time data: a Bayesian perspective. Statistica Sinica 14, 715â€745. G AMERMAN , D. (1997). Sampling from the posterior distribution in generalized linear mixed models. Statistics and Computing 7, 57â€68. G ELMAN , A. (2006). Prior distributions for variance parameters in class-conscious models. Bayesian Analysis 1, 515â€534. H ASTIE , T. J. AND T IBSHIRANI , R. J. (1990). Generalized Additive Models. London: Chapman and Hall. H OBERT, J. P. AND C ASELLA , G. (1996). The effect of improper priors on Gibbs sampling in hierarchical linear mixed models.Journal of the American Statistical Association 91, 1461â€1473. K ASS , R. E. AND S TEFFEY, D. (1989). Approximate Bayesian inference in conditionally independent hierarchical models (parametric empirical Bayes models). Journal of the American Stat istical Association 84, 717â€726. K ELSALL , J. E. AND WAKEFIELD , J. C. (1999). Discussion of â€Å"Bayesian models for spatially correlated disease and exposure data” by N. Best, I. Waller, A. Thomas, E. Conlon and R. Arnold. In: Bernardo, J. M. , Berger, J. O. , Dawid, A. P. and Smith, A. F. M. (editors), Sixth Valencia International Meeting on Bayesian Statistics. London: Oxford University Press.M C C ULLAGH , P. AND N ELDER , J. A. (1989). Generalized one-dimensional Models, 2nd edition. London: Chapman and Hall. M C C ULLOCH , C. E. , S EARLE , S. R. AND N EUHAUS , J. M. (2008). Generalized, Linear, and Mixed Models, 2nd edition. New York: John Wiley and Sons. M ENG , X. AND W ONG , W. (1996). Simulating ratios of normalizing constants via a simple identity. Statistical Sinica 6, 831â€860. NATARAJAN , R. AND K ASS , R. E. (2000). Reference Bayesian methods for generalized linear mixed models. Journal of the American Statistical Association 95, 227â€237. N ELDE R , J. AND W EDDERBURN , R. (1972). Generalized linear models.Journal of the Royal Statistical Society, serial publication A 135, 370â€384. P INHEIRO , J. C. AND BATES , D. M. (2000). Mixed-Effects Models in S and S-plus. New York: Springer. P LUMMER , M. (2008). Penalized prejudice functions for Bayesian model comparison. Biostatistics 9, 523â€539. P LUMMER , M. (2009). Jags version 1. 0. 3 manual. Technical Report. RUE , H. AND H ELD , L. (2005). Gaussian Markov Random Fields: Thoery and Application. Boca Raton: Chapman and Hall/CRC. RUE , H. , M ARTINO , S. AND C HOPIN , N. (2009). Approximate Bayesian inference for possible Gaussian models using integrated nested laplace approximations (with discussion).Journal of the Royal Statistical Society, Series B 71, 319â€392. 412 RUPPERT, D. R. , WAND , M. P. University Press. AND Y. F ONG AND OTHERS C ARROLL , R. J. (2003). Semiparametric Regression. New York: Cambridge S KENE , A. M. AND WAKEFIELD , J. C. (1990). Hierarchica l models for multi-centre binary response studies. Statistics in Medicine 9, 919â€929. S PIEGELHALTER , D. , B EST, N. , C ARLIN , B. AND VAN DER L INDE , A. (1998). Bayesian measures of model complexity and fit (with discussion). Journal of the Royal Statistical Society, Series B 64, 583â€639. S PIEGELHALTER , D. J. , T HOMAS , A.AND B EST, N. G. (1998). WinBUGS drug user Manual. Version 1. 1. 1. Cambridge. T HALL , P. F. AND VAIL , S. C. (1990). Some covariance models for longitudinal count data with overdispersion. Biometrics 46, 657â€671. V ERBEKE , G. V ERBEKE , G. AND AND Downloaded from http://biostatistics. oxfordjournals. org/ at Cornell University Library on April 20, 2013 M OLENBERGHS , G. (2000). Linear Mixed Models for Longitudinal Data. New York: Springer. M OLENBERGHS , G. (2005). Models for clear-cut Longitudinal Data. New York: Springer. WAKEFIELD , J. C. (2007). Disease mapping and spatial regression with count data.Biostatistics 8, 158â€183. WAKEFIEL D , J. C. (2009). Multi-level modelling, the ecologic fallacy, and hybrid study designs. International Journal of Epidemiology 38, 330â€336. WAND , M. P. AND O RMEROD , J. T. (2008). On semiparametric regression with O’Sullivan penalised splines. Australian and New Zealand Journal of Statistics 50, 179â€198. Z EGER , S. L. AND K ARIM , M. R. (1991). Generalized linear models with random effects: a Gibbs sampling approach. Journal of the American Statistical Association 86, 79â€86. [Received September 4, 2009; revise November 4, 2009; accepted for publication November 6, 2009]\r\n'

'The Teachers Place In Society Education Essay\r'

'The teacher ‘s topographic point in society is of critical present momentance. He acts as a pivot for the transmittal of rational traditions and proficient graspments from contemporaries to coevals and helps to maintain the lamp of civilisation combustion. The teachers be liter constantlyyy the supreme authorities of a state ‘s fate. He is being re grow a go at itd as the more or less critical factor in the educational system. Upon his preparednessaration, committedness and efficiency stands the whole construction of centering. He is the tell apart of quality instruction and the surrogate parent of the kid. baby bird run intos to him for cognizance, wisdom, agencys ethical motives inspiration, and what non.\r\nA teacher performs many a(prenominal) maps in the schoolroom for the comprehensive development of the students. teacher maintain the pupils safe, make up one(a)s mind what is of substance for pupils to larn, show a rich and organized constituen t(a) structure of information to the pupils, protect and better the pupils ‘ self-pride, egress an surroundings for the pupils to research a garland of get downs, concern pupils use computing machines and other technology-related tools to carry by dint of specific undertakings, arrange the pupils ‘ environs to maximise the notice that they will larn what you want them to larn, do true pupils are watchful for the find bulge outing degree of their instruction, do certain pupils jibe what other people ( national, province, and/or territory educational professionals ; parents ) think is of write for them to larn, sleep with and foster the pupils.\r\nIn site to successfully accomplish the above-named maps, a instructor ask to print as a betokenor in his/her schoolroom. In other words, the instructor should possess some of importing managerial executions. A director is usually defined as person who is in charge of his/her ecesis and is responsible for t he proper endureing the organising in both facet. Among the 10 direction functions that Henry Mintzberg ( 1973 ) identify in his thesis entitled â€Å" The Nature of Managerial give way ” , he suggested eight set of managerial acquirements, to wit :\r\nPeer readinesss\r\n attractership cl of all timenesss\r\nConflict Resolution acquirements\r\n culture Processing aptitudes\r\nSkills in Decision-Making Under Ambiguity\r\n mental imagery Allocation Skills\r\nEntrepreneurial Skills\r\nIntrospection Skills\r\nChapter Two †requirement Managerial Skills for instructors\r\nHarmonizing to the Oxford lexicon, a feat is defined to be the ability to make something pricy or an expertness. In add-on, a accomplishment is an facet of behavior that bunghole be learnt. In the undermentioned lines, the different managerial accomplishments that are indispens equal to(p), in my sentiment, for a instructor so as to supply the exceed encyclopaedism environment for his/her pupi ls will be elaborated.\r\n2.1 Skill whizz: Leadership Skill\r\nSharma ( 2002 ) believes that the function of the instructor is really of import and he/she demands to move as a leader in his/her schoolroom. Associating to Mintzberg ( 1973 ) , this accomplishment is concerned with the ability of the instructor to show up and assist his/her pupils and at the aforementioned(prenominal) truncate, to interbreed with their dividing lines efficaciously. For those pupils who are per se motivated, the instructor merely acts as an instigator and a facilitator. However, for those pupils who are non motivated ( and harmonizing to my experience, in that respect is a big bulk of them ) , the instructor ‘s leading function is critical of import to actuate those pupils. Motivation, harmonizing to me, toilet be defined as a force that awakes a individual from his/her sleepy vogue to force him/her in an active and dynamic manner. Lavoie ( 2011 ) identified eight forces that motivate pe ople, viz. , gregariousness, liberty, pose, curiousness, ( positive ) aggression, power, identification and association.\r\nBing a Mathematics instructor, in my sentiment, the undermentioned schemes can be adopted to actuate the pupils:\r\nThe instructor himself/herself mustiness be seen as being motivated\r\nTeacher motive can be defined as â€Å" willingness, thrust or desire to prosecute in trus dickensrthy instruction ” ( Michaelowa, 2002, p.5 ) . Hence, mathematically talking, teacher, motive is equal to efficient instruction and accordingly, efficient acquisition.\r\nFind accommodate ways to do pupils love the topic\r\nOne of the grounds wherefore some pupils dis resembling mathematics and happen it deadening is the fact that they do non cognize about its application in real-life. Hence, the instructor need to teach the pupils about the real-life application of mathematics on the premier twenty-four hours to do them cognizant of its sizeableness in the mundane life and how, without mathematics, many things would be unattainable or about impossible.\r\nState the purposes and aims of the undefendable affair\r\nThis should be done on the first twenty-four hours of the class. It is of import to do them aware what is pass judgment from them and in bend, what qualities or behaviours they are expected to hold water at the storage of the class twelvemonth.\r\nLet the pupils go to bed that the instructor is ever available whenever person is holding troubles in his surveies.\r\nSet-up the schoolroom regulations and ordinances in coaction with the pupils.\r\n ingestion different instruction manners in place to fit the several(a) larning manners of the pupils.\r\nIn baffle to extrinsically actuate the pupils, the instructor can assure his/her pupils that the best two among them will be rewarded at the terminal of each term. Of class, the instructor needs to maintain his promise.\r\n2.2 Skill Two: Peer Skill\r\nPeer accomplishment would ment ion to the ability of the instructor to move, at one garb, as a director of the schoolroom and at another garment, as a friend to his/her pupils. This warm relationship should be to some bound and the pupils should be made cognizant of it. Otherwise, being excessively couthy would do pandemonium and undiscipline in the stratum and later, the larning environment of the kin would be to a huge extent and severely affected.\r\nIn general, a pupil, same any other individual, has a demand to experience a sentiency of belongingness to his/her category, his/her classmates every bit sober as his/her instructor. Research has shown that when a pupil feels he/she ‘belongs ‘ to the category, he/she has a higher grade of ingrained motive and has more assurance academically. Freeman et Al. ( 2007 ) claimed that, harmonizing to pupils, their sense of belongingness for a category is raised by a instructor that demonstrates heats and openness, encourages pupil engagement, is en thusiastic, friendly and helpful, and is organised and prepared for category.\r\n2.3 Skill Three: Conflict Resolution Skill\r\nLife in a schoolroom is non ever sweet. On and off, things get rancid between the pupils or even between the pupil and the instructor for diverse grounds. Classroom struggles, may it be a venial or a major one, must be dealt with every bit shortly as they hoist so as to forestall the state of personal business from acquiring out of control. Otherwise, they would botch the instruction and larning environment of the schoolroom.\r\nFor minor instances, the instructor needs to utilize his/her managerial accomplishments of go-between and negotiant rapidly and reasonably. The first verse is to garner information about the causes of the incident, guaranting that the information obtained is from true(a) beginnings. The 2nd measure would be to listen attentively to both students/groups. The last measure would be to figure out jointly with those involved towards a solution. In my sentiment, by continuing in this manner, the pupils would experience closer to their instructor in that they know they can swear their instructor and at the same prison term, they are larning this really of import accomplishment of deciding struggles, which they may use it later in their ain life. In line with the above, Feldman ( 1989 ) argues that pupils would be more positively disposed to the schoolroom activities and to the instructor if they think that the instructor cares about them.\r\nHowever, for major instances of undiscipline, such as sexual maltreatment, the instructor needs to follow the regulations and ordinances of the school lawsuit. The best solution would be to direct those involved to the Discipline Master who would cover with them consequently.\r\n2.4 Skill Four: Information Processing Skill\r\nThis accomplishment is about the instructor ‘s ability to get in out, collect and portion information relevant to the undefendable affair o r subject. In the traditional position of instruction and acquisition, the instructor was the exclusive beginning of cognition and hence, the category was dominantly teacher-oriented. However, despite the fact that this attack to encyclopaedism and acquisition is regarded as being disused, some topics, like mathematics, are most of the clip teacher-centred. But, a good mathematics instructor would happen ways to do his/her category an gratifying and fruitful experience.\r\nPersonally, since about all subjects are inter-related in mathematics, I ever start a subject by giving the basal information and from that, other regulations are derived with the aid of the pupils. In this manner, the instruction manner is shifted from the expository one to a more synergistic more where each pupil is able to lend something in the building of invigorated cognition. The constructivist attack leads to effectual mathematics learning and larning ( van de Walle, 1995 ) . In add-on, this attack requ ires the pupils to be brooding and to work on their old cognition in ordinate to obtain new cognition. Furthermore, their problem-solving ability is enhanced. Brooks & A ; Brooks ( 1993 ) relate that the followers is implied in a constructivist schoolroom:\r\nStudent liberty and enterprise are accepted and encouraged.\r\nThe instructor asks open-ended inquiries and allows delay clip for responses.\r\nHigher-level thought is encouraged.\r\nStudents are engaged in talks with the instructor and with each other.\r\nStudents are engaged in experiences that challenge hypotheses and promote treatment.\r\nThe category uses natural informations, primal beginnings, manipulatives, and physical, synergistic stuffs.\r\nA good mathematics instructor should be able to utilize a assortment of learning manners in order to do the topic appear interesting and easy, and at the same clip, cater for the different acquisition manners of his/her pupils. For case, to learn the subject Vectors in 3-Di mension, it is really hard for pupils to represent the constructs involved utilizing the traditional attack as the subject is instead an abstract one. But when the job is modelled utilizing entrance technological tools, the pupils are able to visualize the job and accordingly, they learn how to pattern the jobs on their ain utilizing reputation and pencil. Hence, using the right mathematical constructs, they are able to work out any jobs on Vectors in 3-Dimension.\r\n2.5 Skill Five: Resource Allocation Skill\r\nThis skill trades with the instructor ‘s ability to press out off his/her clip decently and to make out to each pupil ‘s encountered troubles. The best manner to accomplish these is through proper lesson preparation. It is true that to contract a lesson is a cumbrous undertaking yet at the terminal of the twenty-four hours, it helps salvage a batch of clip and more things can be done. In fact, it can be said that lesson planning is a one measure rearward and two stairss frontward approach. From past experience, the followers should be taken into servant when fixing a lesson program:\r\n use up out one lesson at a clip\r\nThe purpose and aims of the lesson should be good set and the pupils should be made cognizant of it\r\nSince about all subjects in mathematics is based on some pre-requisites, ever recall those old cognition in order to acquire the pupils in the temper\r\nBased on the trouble of the subject, take a considerable nerve centre of clip to to the full explicate the subject, taking into consideration the jobs pupils are holding and blow no clip to unclutter these misconceptions\r\nAllow pupils to hold sufficient burden of clip to pattern some jobs in category and at the same clip, utilize this ‘free ‘ clip to cover separately with those holding farther jobs\r\n heart and soulmarize the whole lesson\r\nGive a sensible sum of prep\r\nReserve the following session for rectifying prep and for farther pattern ( r emedial plants if needed )\r\nA well-prepared lesson program non merely affect the resource parceling accomplishment but besides the entrepreneurial accomplishment of the teacher-manager as the latter trades with the ability of the instructor to look for jobs and chances that may originate during a lesson and thereof, implement the prerequisite alteration swimmingly. For case, while explicating a subject, the instructor sight that the bulk of pupils are non hold oning the lesson, so, he/she should be able to alter the instruction manner consequently. This is why it is of import to ever hold a excogitation B.\r\n2.6 Skill Six: Introspection Skill\r\nThis peradventure the most of import accomplishment needed by a teacher-manager. It deals with the instructor ‘s ability to speculate upon his/her ain work and the impact it has on his/her pupils. In other words, after each lesson, the instructor needs to self-evaluate himself/herself. Successful rating would be that learning and acquisition has occurred and each pupil has understood the lesson and all plants have been completed. Else, the instructor needs to alter his/her learning schemes and/or behavior in category.\r\nChapter 3 †Decision\r\nTo be a good and effectual instructor, a merge of managerial accomplishments is required by the instructor in order to advance a successful instruction and acquisition environment. It is of import to observe that instructors are born(p) with these accomplishments but it takes clip every bit good as tonss of pattern to get and get the run these accomplishments.\r\n'