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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/22724

Title: A SAS Program Combining R Functionalities to Implement Pattern-Mixture Models
Authors: Bunouf, Pierre
Molenberghs, Geert
Grouin, Jean-Marie
Thijs, Herbert
Issue Date: 2015
Abstract: 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.
Notes: [Bunouf, Pierre] Labs Pierre Fabre, 142 Rue Village Entreprises, F-31670 Labege, France. [Molenberghs, Geert; Thijs, Herbert] Univ Hasselt, I BioStat, Agoralaan Bldg D, B-3590 Diepenbeek, Belgium. [Molenberghs, Geert; Thijs, Herbert] Katholieke Univ Leuven, Agoralaan Bldg D, B-3590 Diepenbeek, Belgium. [Grouin, Jean-Marie] Univ Rouen, INSERM, U657, Rue Lavoisier, F-76821 Mont St Aignan, France.
URI: http://hdl.handle.net/1942/22724
DOI: 10.18637/jss.v068.i08
ISI #: 000384910000001
ISSN: 1548-7660
Category: A1
Type: Journal Contribution
Validation: ecoom, 2017
Appears in Collections: Research publications

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