Multiple Imputation for Propensity Score Analysis with Covariates Missing at Random

Introduction Missing data is a common problem in statistical analysis, and can lead to biased or inefficient estimates if not handled properly. One method for dealing with missing data is multiple imputation, which involves creating multiple plausible values for the missing data and analyzing each imputed dataset separately, before combining the results. In this blog …

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