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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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Version

Install

install.packages('smcfcs')

Monthly Downloads

1,731

Version

2.0.0

License

GPL-3

Issues

10

Pull Requests

1

Stars

12

Forks

8

Maintainer

Jonathan Bartlett

Last Published

March 25th, 2025

Functions in smcfcs (2.0.0)

smcfcs.casecohort

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

Substantive model compatible fully conditional specification imputation of covariates.
ex_cc

Simulated case cohort data
smcfcs.nestedcc

Substantive model compatible fully conditional specification imputation of covariates for nested case control studies
smcfcs.parallel

Parallel substantive model compatible imputation
smcfcs.finegray

Substantive model compatible fully conditional specification imputation of covariates for a Fine-Gray model
smcfcs.dtsam

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

Assess convergence of a smcfcs object
smcfcs.flexsurv

Substantive model compatible fully conditional specification imputation of covariates and event times using flexible parametric survival models
ex_coarsening

Simulated example data with a coarsened factor covariate
ex_lininter

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

Simulated discrete time survival data set
ex_linquad

Simulated example data with continuous outcome and quadratic covariate effects
ex_flexsurv

Simulated example data with time-to-event Weibull outcome and two covariates
ex_compet

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

Simulated example data with binary outcome and quadratic covariate effects
ex_ncc

Simulated nested case-control data
ex_poisson

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

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

Simulated example data with competing risks outcome and partially observed covariates