Multiple imputation

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Multiple imputation

Account for missing data in your sample using multiple imputation. Choose from univariate and multivariate methods to impute missing values in continuous, censored, truncated, binary, ordinal, categorical, and count variables. Then, in a single step, estimate parameters using the imputed datasets, and combine results. Fit a linear model, logit model, Poisson model, multilevel model, survival model, or one of the many other supported models. Use the mi command, or let the Control Panel interface guide you through your entire MI analysis.

Learn about multiple imputation.

Imputation methods

Multivariate normal
Chained equations
Linear regression
Predictive mean matching
Truncated regression
Interval regression
Logistic
Ordered logit
Multinomial (polytomous) logit
Poisson
Negative binomial
User-defined

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.

Utilities

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

Watch handling missing data in Stata tutorials

Setup, imputation, estimation—regression imputation
Setup, imputation, estimation—predictive mean matching
Setup, imputation, estimation—logistic regression imputation

Additional resources

Multiple-Imputation Reference Manual
In the spotlight: Multiple imputation
Handling missing data using multiple imputation training course
Multiple imputation flyer

See New in Stata 18 to learn about what was added in Stata 18.

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