I am using the glimmix procedure in SAS to model a generalize linear mixed model with and binomial distribution and a logit link function. I am modeling both the G-side and the R-side covariance structure due to the nature of my data (repeated measures for 43 participants).
Specifically I use a random intercept model for subjects and G-side covariance matrix following a variance component structure. To account for the repeated measures the model also included random residuals for subjects with the R-side covariance matrix modeled as first order auto regressive.
My question now is; how do I interpret the covariance parameter estimates (an example is provided below))?
Covariance Parameter Estimates
Cov Parm Subject Estimate Standard Error
Intercept Subject 1.233 0.2133
AR(1) Subject 0.1113 0.004561
Residual 0.9964 0.00651
Best Answer
The estimates are just estimates of the parameters specified in the random statements.
($\tau$, $\sigma$ and $\rho$ are used based on notation from e.g. Multilevel Analysis by Snijders & Bosker (2012))
I hope this will help others as well.