Methods for Mediation Analysis with Missing Data

Autor/inn/en	Zhang, Zhiyong; Wang, Lijuan
Titel	Methods for Mediation Analysis with Missing Data
Quelle	In: Psychometrika, 78 (2013) 1, S.154-184 (31 Seiten) PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0033-3123
DOI	10.1007/s11336-012-9301-5
Schlagwörter	Maximum Likelihood Statistics; Structural Equation Models; Simulation; Measurement Techniques; Comparative Analysis; Data Analysis + Suchen Sie Ihr Suchwort? Simulation program; Simulationsprogramm; Messtechnik; Auswertung
Abstract	Despite wide applications of both mediation models and missing data techniques, formal discussion of mediation analysis with missing data is still rare. We introduce and compare four approaches to dealing with missing data in mediation analysis including list wise deletion, pairwise deletion, multiple imputation (MI), and a two-stage maximum likelihood (TS-ML) method. An R package bmem is developed to implement the four methods for mediation analysis with missing data in the structural equation modeling framework, and two real examples are used to illustrate the application of the four methods. The four methods are evaluated and compared under MCAR, MAR, and MNAR missing data mechanisms through simulation studies. Both MI and TS-ML perform well for MCAR and MAR data regardless of the inclusion of auxiliary variables and for AV-MNAR data with auxiliary variables. Although listwise deletion and pairwise deletion have low power and large parameter estimation bias in many studied conditions, they may provide useful information for exploring missing mechanisms. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10