Missing data is an inevitable challenge in empirical research, survey analysis, and data science. Ignoring missing values—often referred to as complete case analysis—can lead to biased estimates and a loss of statistical power. The mi suite in Stata provides a robust, built-in framework for managing, imputing, and analyzing incomplete datasets using Multiple Imputation (MI) techniques.
: Multivariate Normal imputation for continuous variables. mi suite
These are the most polarizing components. Both are built on a Chromium/WebView core and an Exoplayer backend but feature aggressive content feeds. Missing data is an inevitable challenge in empirical
: Identifies complete variables used to predict missingness. 3. Multiple Imputation ( mi impute ) built-in framework for managing