12.9. Summary
Analyzing incomplete (longitudinal) data, both of a Gaussian as well as of a non-Gaussian nature, can easily be conducted under the relatively relaxed assumption of missingness at random (MAR), using standard statistical software tools. Likelihood-based methods include the linear mixed model and generalized linear mixed models. In addition, weighted generalized estimating equations (WGEE) can be used as a relatively straightforward fix up of ordinary generalized estimating equations (GEE) so that also this technique is valid under MAR. Alternative methods which allow for ignoring the missing data mechanism under MAR include multiple imputation (MI) and the Expectation-Maximization (EM) algorithm. The GLIMMIX macro and PROC GLIMMIX ...
Get Pharmaceutical Statistics Using SAS now with the O’Reilly learning platform.
O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.
