How to handle missing data

[mara]

I included some resources in an similar thread here:

Data prediction for missing data

I'm a big fan of this article on Missing Data Imputation (by Andrew Gelman, I believe) which includes R code for various methods, as well: http://www.stat.columbia.edu/~gelman/arm/missing.pdf Packages worth checking out (mentioned in this RViews post by Joseph Rickert, Missing Values, Data Science and R) Amelia implements the Amelia II algorithm which assumes that the complete data set (missing and observed data) are multivariate normal. Imputations are done via the EMB (expectation-maximization with bootstrapping) algorithm. The JSS paper describes a strategy for combining the models resulting from each imputed data set. The Amelia vignette contains examples. BaBoon provides two varian…