Applied Bootstrap Analysis With Imputed Data in Stata

Felix Bittmann

doi:10.20944/preprints202401.0813.v1

Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Version 1 : Received: 9 January 2024 / Approved: 10 January 2024 / Online: 10 January 2024 (10:22:49 CET)

Multiple imputation with chained equations (MICE) is a widespread approach to account for missing data in empirical research. Combining MICE with bootstrapping, that is, repeatedly resampling with replacement from the data to estimate variances and confidence intervals of statistics of interest, is not straightforward. The current document provides an overview of how to use bootstrapping with imputed data in Stata. Two main approaches (impute first and then bootstrap or vice-versa) are discussed and shortly compared. Code is provided for Stata.

bootstrapping; multiple imputation; MICE; stata; missing data

Computer Science and Mathematics, Probability and Statistics

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Applied Bootstrap Analysis With Imputed Data in Stata

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