A SAS program combining R functionalities to implement pattern-mixture models

Pattern-mixture models have gained considerable interest in recent years. pattern-mixture modeling allows the analysis of incomplete longitudinal outcomes under a variety of missingness mechanisms. in this manuscript,we describe a sas program which combines r functionalities to fit pattern-mixture models,considering the cases that missingness mechanisms are at random and not at random. patterns are defined based on missingness at every time point and parameter estimation is based on a full group-by-time interaction. the program implements a multiple imputation method under so-called identifying restrictions. the code is illustrated using data from a placebo-controlled clinical trial. this manuscript and the program are directed to sas users with minimal knowledge of the r language. © 2015,american statistical association. all rights reserved.