Suggested reading - Multiple Imputation for Missing Data


  • Allison P. (2002). Missing Data. Thousand Oaks, California: Sage Publications.
  • Carpenter J, & Kenward MG. (2013). Multiple Imputation and its Application. Chichester: WIley.
  • Graham J. (2012). Missing data: analysis and design. New York: Springer.
  • Molenberghs G, Fitzmaurice G, Kenward MG, Tsiatis A, Verbeke G. (2014). Handbook of Missing Data Methodology. Chapman & Hall.
  • Rubin DB. (1987) Multiple Imputation for Nonresponse in Surveys. New York, NY: John Wiley.
  • Van Buuren, S. (2012), Flexible Imputation of Missing Data. Chapman & Hall.


  • Lee KJ, Simpson JA. Introduction to multiple imputation for dealing with missing data. Respirology 2014; 19:162-167.
  • Ratitch, B., O'Kelly, M. & Tosiello, R. Missing data in clinical trials: from clinical assumptions to statistical analysis using pattern mixture models. Pharmaceutical Statistics 2013; 12(6): 337.
  • Rubin DB. Multiple imputation after 18+ years. Journal of the American Statistical Association 1996; 91(434):473-489.
  • Sterne JAC, White IR, Carlin JB, et al. Multiple imputation for missing data in epidemiological and clinical research: potential and pitfalls. BMJ 2009;338:b2393.
  • VanBuuren S, Boshulzen HC, Knook DL. Multiple imputation of missing blood pressure covariates in survival analysis. Statistics in Medicine 1999; 18: 681-694.
  • White IR, Royston P, Wood AM. Multiple imputation using chained equations: issues and guidance for practice. Statistics in Medicine 2011;30(4):377-399.