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Updated: Aug 8, 2026

Inverse Probability of Treatment Weighting (Propensity Score) using the Military Health System Data Repository and National Death Index
Published on: January 8, 2020
A primer on the use of modern missing-data methods in psychosomatic medicine research
1Arizona State University, Department of Psychology, P.O. Box 871104, Tempe, Aarizona 85287-1104, USA. cenders@asu.edu
Abstract:
This paper summarizes recent methodologic advances related to missing data and provides an overview of two "modern" analytic options, direct maximum likelihood (DML) estimation and multiple imputation (MI). The paper begins with an overview of missing data theory, as explicated by Rubin. Brief descriptions of traditional missing data techniques are given, and DML and MI are outlined in greater detail; special attention is given to an "inclusive" analytic strategy that incorporates auxiliary variables into the analytic model. The paper concludes with an illustrative analysis using an artificial quality of life data set. Computer code for all DML and MI analyses is provided, and the inclusion of auxiliary variables is illustrated.
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