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smcfcs is an R package implementing Substantive Model Compatibly Fully Conditional Specification Multiple Imputation. Examples and further details are given in the package documentation and vignette.

To install the latest GitHub development version, run:

install.packages("devtools")

devtools::install_github("jwb133/smcfcs")

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Install

install.packages('smcfcs')

Monthly Downloads

1,930

Version

1.7.1

License

GPL-3

Issues

11

Pull Requests

1

Stars

11

Forks

7

Maintainer

Jonathan Bartlett

Last Published

November 7th, 2022

Functions in smcfcs (1.7.1)

smcfcs.parallel

Parallel substantive model compatible imputation
smcfcs.casecohort

Substantive model compatible fully conditional specification imputation of covariates for case cohort studies
smcfcs.dtsam

Substantive model compatible fully conditional specification imputation of covariates for discrete time survival analysis
smcfcs

Substantive model compatible fully conditional specification imputation of covariates.
smcfcs.nestedcc

Substantive model compatible fully conditional specification imputation of covariates for nested case control studies
ex_ncc

Simulated nested case-control data
plot.smcfcs

Assess convergence of a smcfcs object
ex_compet

Simulated example data with competing risks outcome and partially observed covariates
ex_cc

Simulated case cohort data
ex_poisson

Simulated example data with count outcome, modelled using Poisson regression
ex_linquad

Simulated example data with continuous outcome and quadratic covariate effects
ex_coxquad

Simulated example data with time to event outcome and quadratic covariate effects
ex_dtsam

Simulated discrete time survival data set
ex_logisticquad

Simulated example data with binary outcome and quadratic covariate effects
ex_lininter

Simulated example data with continuous outcome and interaction between two partially observed covariates