Published by the Foundation for Open Access Statistics Editors-in-chief: Bettina Grün, Torsten Hothorn, Rebecca Killick, Edzer Pebesma, Achim Zeileis    ISSN 1548-7660; CODEN JSSOBK
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Authors: Pierre Bunouf, Geert Molenberghs, Jean-Marie Grouin, Herbert Thijs
Title: A SAS Program Combining R Functionalities to Implement Pattern-Mixture Models
Abstract: Pattern-mixture models have gained considerable interest in recent years. Patternmixture 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-bytime 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.

Page views:: 1204. Submitted: 2013-02-20. Published: 2015-12-27.
Paper: A SAS Program Combining R Functionalities to Implement Pattern-Mixture Models     Download PDF (Downloads: 2281)
Supplements: Source code and replication materials Download (Downloads: 134; 35KB)

DOI: 10.18637/jss.v068.i08

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Paper: Creative Commons Attribution 3.0 Unported License
Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license.