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| Publisher: | Stata Press |
| Copyright: | 2025 |
| ISBN-13: | 978-1-59718-437-3 |
| Pages: | 400 |
Suggested citation:
StataCorp. 2025. Stata 19 Multiple-Imputation Reference Manual. College Station, TX: Stata Press.
Handling missing data using multiple imputation training course
| Intro substantive | Introduction to multiple-imputation analysis |
| Intro | Introduction to mi |
| Estimation | Estimation commands for use with mi estimate |
| mi add | Add imputations from another mi dataset |
| mi append | Append mi data |
| mi convert | Change style of mi data |
| mi copy | Copy mi flongsep data |
| mi describe | Describe mi data |
| mi erase | Erase mi datasets |
| mi estimate | Estimation using multiple imputations |
| mi estimate using | Estimation using previously saved estimation results |
| mi estimate postestimation | Postestimation tools for mi estimate |
| mi expand | Expand mi data |
| mi export | Export mi data |
| mi export ice | Export mi data to ice format |
| mi export nhanes1 | Export mi data to NHANES format |
| mi extract | Extract original or imputed data from mi data |
| mi import | Import data into mi |
| mi import flong | Import flong-like data into mi |
| mi import flongsep | Import flongsep-like data into mi |
| mi import ice | Import ice-format data into mi |
| mi import nhanes1 | Import NHANES-format data into mi |
| mi import wide | Import wide-like data into mi |
| mi impute | Impute missing values |
| mi impute chained | Impute missing values using chained equations |
| mi impute intreg | Impute using interval regression |
| mi impute logit | Impute using logistic regression |
| mi impute mlogit | Impute using multinomial logistic regression |
| mi impute monotone | Impute missing values in monotone data |
| mi impute mvn | Impute using multivariate normal regression |
| mi impute nbreg | Impute using negative binomial regression |
| mi impute ologit | Impute using ordered logistic regression |
| mi impute pmm | Impute using predictive mean matching |
| mi impute poisson | Impute using Poisson regression |
| mi impute regress | Impute using linear regression |
| mi impute truncreg | Impute using truncated regression |
| mi impute usermethod | User-defined imputation methods |
| mi merge | Merge mi data |
| mi misstable | Tabulate pattern of missing values |
| mi passive | Generate/replace and register passive variables |
| mi predict | Obtain multiple-imputation predictions |
| mi ptrace | Load parameter-trace file into Stata |
| mi rename | Rename variable |
| mi replace0 | Replace original data |
| mi reset | Reset imputed or passive variables |
| mi reshape | Reshape mi data |
| mi select | Programmer's alternative to mi extract |
| mi set | Declare multiple-imputation data |
| mi stsplit | Split and join time-span records for mi data |
| mi test | Test hypotheses after mi estimate |
| mi update | Ensure that mi data are consistent |
| mi varying | Identify variables that vary across imputations |
| mi xeq | Execute command(s) on individual imputations |
| mi XXXset | Declare mi data to be svy, st, ts, xt, etc. |
| noupdate option | The noupdate option |
| Styles | Dataset styles |
| Technical | Details for programmers |
| Workflow | Suggested workflow |
| Glossary | |
| Combined author index | |
| Combined subject index | |
