Imputation methods

Multivariate normal

Chained equations

Linear regression

Predictive mean matching

Truncated regression

Interval regression


Ordered logit

Multinomial (polytomous) logit


Negative binomial



Data management

Tabulate missing values

Create summary variables of missing-value patterns

Identify varying and super-varying variables

Execute commands across imputations

Export and import foreign data

Create functions of imputed variables


Estimation and inference

Automatically pool results from each dataset

Joint tests of coefficients

Linearly and nonlinearly transformed coefficients

Linear and nonlinear MI predictions


Postestimation Selector

View and run all postestimation features for your command

Automatically updated as estimation commands are run

Watch Postestimation Selector.



Change style of multiple-imputation datasets

Extract datasets

Verify and repair consistency of data


Learn more

Introduction to mi

Introduction to multiple-imputation analysis

Control Panel

Guides you along from start to finish

Set up data and impute missing values or import data

Perform data management

Perform estimation and inference

Command log produced to ensure reproducibility


MI Control Panel


Watch handling missing data in Stata tutorials



Additional resources

In the spotlight: Multiple imputation