>> Home >> Products >> Features >> Multiple imputation

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

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


  • 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

The Stata Blog: Not Elsewhere Classified Find us on Facebook Follow us on Twitter LinkedIn Google+ Watch us on YouTube