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: Delia C. Voronca, Mulugeta Gebregziabher, Valerie Durkalski-Mauldin, Lei Liu, Leonard E. Egede
Title: MTPmle: A SAS Macro and Stata Programs for Marginalized Inference in Semi-Continuous Data
Abstract: We develop a SAS macro and equivalent Stata programs that provide marginalized inference for semi-continuous data using a maximum likelihood approach. These software extensions are based on recently developed methods for marginalized two-part (MTP) models. Both the SAS and Stata extensions can fit simple MTP models for cross-sectional semi-continuous data. In addition, the SAS macro can fit random intercept models for longitudinal or clustered data, whereas the Stata programs can fit MTP models that account for subject level heteroscedasticity and for a complex survey design. Differences and similarities between the two software extensions are highlighted to provide a comparative picture of the available options for estimation, inclusion of random effects, convergence diagnosis, and graphical display. We provide detailed programming syntax, simulated and real data examples to facilitate the implementation of the MTP models for both SAS and Stata software users.

Page views:: 2135. Submitted: 2016-01-11. Published: 2018-11-12.
Paper: MTPmle: A SAS Macro and Stata Programs for Marginalized Inference in Semi-Continuous Data     Download PDF (Downloads: 1356)
Supplements: SAS and Stata software including replication materials Download (Downloads: 148; 1MB)

DOI: 10.18637/jss.v087.i06

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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.