What? All the players know there are three major ways to handle missing data: full-information maximum likelihood, multiple imputation, and one-step full-luxury1 Bayesian imputation. In an earlier post, we walked through method for plotting the fitted lines from models fit with multiply-imputed data. In this post, we’ll discuss another neglected topic: How might one compute standardized regression coefficients from models fit with multiply-imputed data? I make assumptions. For this post, I...
