Intro to Generalized Linear Models

Generalized linear models are extensions of classical linear models. Classes of generalized linear models include linear regression, logistic regression for binary and binomial data, nominal and ordinal multi-nomial logistic regression, Poisson regression for count data and Gamma regression for data with constant coefficient of variation.

Generalized Estimating Equations (GEE) provide an efficient method to analyze repeated measures where the normality assumption does not hold.

In SAS there are > 10 procedures that will fit a linear regression, example:

title " Simple linear regression of Income " ;
proc reg data = IM ;
model Inc = EN Lit US5 ;
output out = OutIm ( keep = Nation LInc Inc En Lit US5 r lev cd dffit )
rstudent = r h = lev cookd = cd dffits = dffit ;
run ;
quit ;