Package: ImputeLongiCovs 0.1.0
ImputeLongiCovs: Longitudinal Imputation of Categorical Variables via a Joint Transition Model
Imputation of longitudinal categorical covariates. We use a methodological framework which ensures that the plausibility of transitions is preserved, overfitting and colinearity issues are resolved, and confounders can be utilized. See Mamouris (2023) <doi:10.1002/sim.9919> for an overview.
Authors:
ImputeLongiCovs_0.1.0.tar.gz
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ImputeLongiCovs.pdf |ImputeLongiCovs.html✨
ImputeLongiCovs/json (API)
| # Install 'ImputeLongiCovs' in R: |
| install.packages('ImputeLongiCovs', repos = c('https://pmamouris.r-universe.dev', 'https://cloud.r-project.org')) |
- analyses_data - Analyses Data for imputing categorical covariates
- initial_data - Initial Data for imputing categorical covariates
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 1 years agofrom:be25a6c63e. Checks:OK: 3 NOTE: 4. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 22 2024 |
| R-4.5-win | NOTE | Nov 22 2024 |
| R-4.5-linux | NOTE | Nov 22 2024 |
| R-4.4-win | NOTE | Nov 22 2024 |
| R-4.4-mac | NOTE | Nov 22 2024 |
| R-4.3-win | OK | Nov 22 2024 |
| R-4.3-mac | OK | Nov 22 2024 |
Exports:create_probMatriximpute_categorical_covariates
Dependencies:nnet
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Analyses Data for imputing categorical covariates | analyses_data |
| create_probMatrix | create_probMatrix |
| impute_categorical_covariates | impute_categorical_covariates |
| Initial Data for imputing categorical covariates | initial_data |
