Mediation Analysis with Missing Data Through Multiple Imputation and Bootstrap
- 1.9k Downloads
A method using multiple imputation and bootstrap for dealing with missing data in mediation analysis is introduced and implemented in both SAS and R. Through simulation studies, it is shown that the method performs well for both MCAR and MAR data without and with auxiliary variables. It is also shown that the method can work for MNAR data if auxiliary variables related to missingness are included. The application of the method is demonstrated through the analysis of a subset of data from the National Longitudinal Survey of Youth. Mediation analysis with missing data can be conducted using the provided SAS macros and R package bmem.
KeywordsMediation analysis Missing data Multiple imputation Bootstrap
- Center for Human Resource Research. (2006). NLSY79 CHILD & YOUNG ADULT DATA USERS GUIDE: A Guide to the 1986–2004 Child Data. Columbus, OH: The Ohio State UniversityGoogle Scholar
- Freedman, L. S., & Schatzkin, A. (1992). Sample size for studying intermediate endpoints within intervention trails or observational studies. American Journal of Epidemiology, 136, 1148–1159.Google Scholar
- MacKinnon, D. P. (2008). Introduction to statistical mediation analysis. New York, NY: Taylor & Francis.Google Scholar
- Sobel, M. E. (1982). Asymptotic confidence intervals for indirect effects in structural equation models. In S. Leinhardt (Ed.), Sociological methodology (pp. 290–312). San Francisco: Jossey-Bass.Google Scholar
- Sobel, M. E. (1986). Some new results on indirect effects and their standard errors in covariance structure models. In N. Tuma (Ed.), Sociological methodology (pp. 159–186). Washington, DC: American Sociological Association.Google Scholar
- Wang, L., Zhang, Z., & Estabrook, R. (2009). Longitudinal mediation analysis of training intervention effects. In S. M. Chow, E. Ferrer, & F. Hsieh (Eds.), Statistical methods for modeling human dynamics: An interdisciplinary dialogue (pp. 349–380). New Jersey: Lawrence Erlbaum Associates.Google Scholar
- Woodworth, R. S. (1928). Dynamic psychology. In C. Murchison (Ed.), Psychologies of 1925 (pp. 111–126). Worcester, MA: Clark Universal Academy Press, Inc.Google Scholar
- Wu, S. S., Willcutt, E., Escovar, E., & Menon, V. (2014). Mathematics achievement, anxiety and their relation to internalizing and externalizing behaviors. Journal of Learning Disorders, 47(6), 503–514.Google Scholar
- Zhang, Z., & Wang, L. (2008). Methods for evaluating mediation effects: Rationale and comparison. In K. Shigemasu, A. Okada, T. Imaizumi, & T. Hoshino (Eds.), New trends in psychometrics (pp. 595–604). Tokyo: Universal Academy Press, Inc.Google Scholar
- Zhang, Z., & Wang, L. (2013a). bmem: Mediation analysis with missing data using bootstrap. R package version 1.5. https://cran.r-project.org/web/packages/bmem/index.html.