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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

1,714

Version

1.9.2

License

GPL-3

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Maintainer

Jonathan Bartlett

Last Published

January 21st, 2025

Functions in smcfcs (1.9.2)

ex_poisson

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

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

Assess convergence of a smcfcs object
ex_linquad

Simulated example data with continuous outcome and quadratic covariate effects
smcfcs.nestedcc

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

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

Parallel substantive model compatible imputation
smcfcs.dtsam

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

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

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

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

Simulated case cohort data
ex_coxquad

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

Simulated discrete time survival data set
ex_flexsurv

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

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_compet

Simulated example data with competing risks outcome and partially observed covariates