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proc genmod data= ;

class ;


repeated subject= / corr= type=   ;

lsmeans x / diff=control ('ref') cl adjust=Dunnett(or tukey);



Parameters estimated with maximum likelihood methods. This is an iterative process, i.e., the computer adjusts the parameter until the log likelihood function is maximised. 

DistributionLink functionNote
normalidentitycontinuous dependent variable, mean difference
binomiallogrisk ratio from exponentiation of the parameter estimate 
binomiallogitodds ratio
poissonlogrisk ratio from exponentiation of the parameter estimate; used for robust error estimate with repeated subject statement


categorical response variable with more than two levels 

Sums of squaresEffect typeNote
Type ISequentialThe SS for each factor is the incremental improvement in the error SS as each factor
effect is added to the model. In other words it is the effect as the factor were
considered one at a time into the model, in the order they are entered in the model
Type IIHierarchical or partially sequentialThe SS for each factor is the reduction in residual error obtained by adding that term to a model consisting of all other terms that do not contain the term in question.
Type IIIMarginalThe effect of each variable is evaluated after all other factors have been accounted for.

Repeated statement: specifies the covariance structure of multivariate responses and iterative fitting algorithm for GEE model fitting.