Based on the structure of the model, the GLIMMIX procedure selects the estimation technique for estimating the model parameters. If you fit a generalized linear mixed model, you can change the estimation technique with the METHOD= option in the PROC GLIMMIX statement. The defaults are determined as follows:
generalized linear model
normal distribution: restricted maximum likelihood
all other distributions: maximum likelihood
generalized linear model with overdispersion Parameters (; , if present) are estimated by (restricted) maximum likelihood as for generalized linear models. The overdispersion parameter is estimated from the Pearson statistic after all other parameters have been estimated.
generalized linear mixed models The default technique is METHOD =RSPL, corresponding to maximizing the residual log pseudo-likelihood with an expansion about the current solutions of the best linear unbiased predictors of the random effects. In models for normal data with identity link, METHOD= RSPL and METHOD= RMPL are equivalent to restricted maximum likelihood estimation, and METHOD= MSPL and METHOD= MMPL are equivalent to maximum likelihood estimation. This is reflected in the labeling of statistics in the "Fit Statistics" table.