February 2007
Beginner to intermediate
464 pages
16h
English
book
Pharmaceutical Statistics Using SAS
by Ph. D. Alex Dmitrienko, Ph. D. Christy Chuang-Stein, Sr. Ralph B. D'Agostino
Content preview from Pharmaceutical Statistics Using SAS
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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 ...
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