overdispersion and quasibinomial model
djpren wrote:
Thanks for the reply. Naturally I already searched the site and help for the answers to these questions. I think I've figured out how to run a quasi-binomial model, but I cannot figure out how to test for over-dispersion or how to apply a shapiro-wilk test. This is not homework, neither do I have an instructor who is proficient in using R. This program was suggested to me by another researcher after he witnessed my frustration with the inflexibility of SPSS and other such programs. I am on a very tight schedule and I don't have time to become a statistician and computer scientist, which is why I wrote 3 very quick questions asking for commands that i had already tried to find myself. Testing for over-dispersion is probably something I can eventually get to grips with, since I just have get variance for the real and modelled data. However, I cannot find a command to do shapiro-wilks on the site or on these forums. Also, why do you say that most people here wouldn't recommend this procedure?
??shapiro stats::shapiro.test Shapiro-Wilk Normality Test (maybe you were searching for "shapiro-wilks" (sic)?) People often disrecommend statistical tests of normality because they have low power for small data sets (hence you don't have power to detect non-normality when it is present) and high power for large data sets even when the degree of non-normality detected is not enough to invalidate the results of some statistical procedures. Under what circumstances are the residuals from a quasibinomial GLM expected to be normally distributed ... ?
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