How to Use SPSS-Replacing Missing Data Using Multiple Imputation (Regression Method)

Technique for replacing missing data using the regression method. Appropriate for data that may be missing randomly or non-randomly. Also appropriate for data that will be used in inferential analysis. Determining randomness of missing data can be confirmed with Little's MCAR Test (http://youtu.be/6ybgVTabJ6s).

Resources:
FAQ- http://sites.stat.psu.edu/~jls/mifaq.html

Schafer, Joseph L. "Multiple imputation: a primer." Statistical methods in medical research 8.1 (1999): 3-15.

Sterne, Jonathan AC, et al. "Multiple imputation for missing data in epidemiological and clinical research: potential and pitfalls." BMJ: British Medical Journal 338 (2009).

McKnight, Patrick E., Katherine M. McKnight, and Aurelio Jose Figueredo. Missing data: A gentle introduction. Guilford Press, 2007.

Haukoos, Jason S., and Craig D. Newgard. "Advanced statistics: missing data in clinical research—part 1: an introduction and conceptual framework." Academic Emergency Medicine 14.7 (2007): 662-668.

Newgard, Craig D., and Jason S. Haukoos. "Advanced statistics: missing data in clinical research—part 2: multiple imputation." Academic Emergency Medicine 14.7 (2007): 669-678.