Package: mi 1.1
mi: Missing Data Imputation and Model Checking
The mi package provides functions for data manipulation, imputing missing values in an approximate Bayesian framework, diagnostics of the models used to generate the imputations, confidence-building mechanisms to validate some of the assumptions of the imputation algorithm, and functions to analyze multiply imputed data sets with the appropriate degree of sampling uncertainty.
Authors:
mi_1.1.tar.gz
mi_1.1.zip(r-4.5)mi_1.1.zip(r-4.4)mi_1.1.zip(r-4.3)
mi_1.1.tgz(r-4.4-any)mi_1.1.tgz(r-4.3-any)
mi_1.1.tar.gz(r-4.5-noble)mi_1.1.tar.gz(r-4.4-noble)
mi_1.1.tgz(r-4.4-emscripten)mi_1.1.tgz(r-4.3-emscripten)
mi.pdf |mi.html✨
mi/json (API)
| # Install 'mi' in R: |
| install.packages('mi', repos = c('https://bgoodri.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 2 years agofrom:d2eadcfdcb. Checks:OK: 1 WARNING: 6. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Sep 16 2024 |
| R-4.5-win | WARNING | Sep 16 2024 |
| R-4.5-linux | WARNING | Sep 16 2024 |
| R-4.4-win | WARNING | Sep 16 2024 |
| R-4.4-mac | WARNING | Sep 16 2024 |
| R-4.3-win | WARNING | Sep 16 2024 |
| R-4.3-mac | WARNING | Sep 16 2024 |
Exports:.possible_missing_variable.prunechangechange_familychange_imputation_methodchange_linkchange_modelchange_sizechange_transformationchange_typecompletedisplayfit_modelget_parametershistimagemimi2BUGSmi2statamipplymissing_data.framemissing_variablemultinomialplotpoolrdata.frameRhats
Dependencies:abindarmbootcodalatticelme4MASSMatrixminqanlmenloptrRcppRcppEigen
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Iterative Multiple Imputation from Conditional Distributions | mi-package |
| Class "missing_variable" and Inherited Classes | 01missing_variable MatrixTypeThing-class missing_variable missing_variable-class WeAreFamily-class |
| Class "missing_data.frame" | 02missing_data.frame missing_data.frame missing_data.frame-class |
| Make Changes to Discretionary Characteristics of Missing Variables | 03change change change-methods change_family change_imputation_method change_link change_model change_size change_transformation change_type |
| Multiple Imputation | 04mi mi mi-class mi-methods |
| Convergence Diagnostics | 05Rhats mi2BUGS Rhats |
| Estimate a Model Pooling Over the Imputed Datasets | 06pool display,pooled-method pool pooled-class pooled-methods |
| Extract the Completed Data | 07complete complete complete-methods |
| Class "allcategorical_missing_data.frame" | allcategorical_missing_data.frame allcategorical_missing_data.frame-class |
| Class "bounded-continuous" | bounded-continuous bounded-continuous-class |
| Class "categorical" and Inherited Classes | binary-class categorical categorical-class grouped-binary-class interval-class ordered-categorical-class unordered-categorical-class |
| The "censored-continuous" Class, the "truncated-continuous" Class and Inherited Classes | censored-continuous censored-continuous-class FF_censored-continuous-class FF_truncated-continuous-class FN_censored-continuous-class FN_truncated-continuous-class NF_censored-continuous-class NF_truncated-continuous-class NN_censored-continuous-class NN_truncated-continuous-class truncated-continuous truncated-continuous-class |
| Subset of variables from the CHAIN project | CHAIN |
| Class "continuous" | continuous continuous-class |
| Class "count" | count-class |
| Class "experiment_missing_data.frame" | experiment_missing_data.frame experiment_missing_data.frame-class |
| Wrappers To Fit a Model | fit_model fit_model-methods |
| An Extractor Function for Model Parameters | get_parameters get_parameters-methods |
| Histograms of Multiply Imputed Data | hist hist-methods |
| Class "irrelevant" and Inherited Classes | fixed-class group-class irrelevant irrelevant-class |
| Exports completed data in Stata (.dta) or comma-separated (.csv) format | mi2stata |
| Apply a Function to a Object of Class mi | mipply |
| Class "multilevel_missing_data.frame" | multilevel_missing_data.frame multilevel_missing_data.frame-class |
| The multinomial family | multinomial |
| National Longitudinal Survey of Youth Extract | nlsyV |
| Class "positive-continuous" and Inherited Classes | positive-continuous-class proportion-class |
| Generate a random data.frame with tunable characteristics | rdata.frame |
| Class "semi-continuous" and Inherited Classes | nonnegative-continuous nonnegative-continuous-class SC_proportion SC_proportion-class semi-continuous semi-continuous-class |
