The parameter in the loglikelihood functions is a scale parameter. McCullagh and Nelder (1989, p. 29) refer to it as the dispersion parameter. With the exception of the normal distribution, does not correspond to the variance of an observation, the variance of an observation in a generalized linear model is a function of and . In a generalized linear model (GLM mode), the GLIMMIX procedure displays the estimate of is as “Scale” in the “Parameter Estimates” table. Note that for some distributions this scale is different from that reported by the GENMOD procedure in its “Parameter Estimates” table. The scale reported by PROC GENMOD is sometimes a transformation of the dispersion parameter in the loglikelihood function. Table 43.21 displays the relationship between the “Scale” entries reported by the two procedures in terms of the (or k) parameter in the GLIMMIX loglikelihood functions.
Table 43.21: Scales in Parameter Estimates Table
Distribution 
GLIMMIX Reports 
GENMOD Reports 

Beta 

N/A 
Gamma 


Inverse Gaussian 


Negative binomial 


Normal 


Note that for normal linear models, PROC GLIMMIX by default estimates the parameters by restricted maximum likelihood, whereas PROC GENMOD estimates the parameters by maximum likelihood. As a consequence, the scale parameter in the “Parameter Estimates” table of the GLIMMIX procedure coincides for these models with the meansquared error estimate of the GLM or REG procedures. To obtain maximum likelihood estimates in a normal linear model in the GLIMMIX procedure, specify the NOREML option in the PROC GLIMMIX statement.