smcfcs - Multiple Imputation of Covariates by Substantive Model Compatible Fully Conditional Specification
Implements multiple imputation of missing covariates by Substantive Model Compatible Fully Conditional Specification. This is a modification of the popular FCS/chained equations multiple imputation approach, and allows imputation of missing covariate values from models which are compatible with the user specified substantive model.
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9.00 score 14 stars 1 dependents 83 scripts 4.0k downloadsgFormulaMI - G-Formula for Causal Inference via Multiple Imputation
Implements the G-Formula method for causal inference with time-varying treatments and confounders using Bayesian multiple imputation methods, as described by Bartlett et al (2025) <doi:10.1177/09622802251316971>. It creates multiple synthetic imputed datasets under treatment regimes of interest using the 'mice' package. These can then be analysed using rules developed for analysing multiple synthetic datasets.
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5.32 score 9 stars 23 scripts 270 downloadsInformativeCensoring - Multiple Imputation for Informative Censoring
Multiple Imputation for Informative Censoring. This package implements two methods. Gamma Imputation described in <DOI:10.1002/sim.6274> and Risk Score Imputation described in <DOI:10.1002/sim.3480>.
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4.82 score 1 stars 1 dependents 11 scripts 328 downloadsbootImpute - Bootstrap Inference for Multiple Imputation
Bootstraps and imputes incomplete datasets. Then performs inference on estimates obtained from analysing the imputed datasets as proposed by von Hippel and Bartlett (2021) <doi:10.1214/20-STS793>.
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3.48 score 2 stars 4 scripts 439 downloads