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InformativeCensoring

Multiple Imputation for Informative Censoring

This R package implement two methods for multiple imputation of survival data.

  • Gamma imputation from Jackson et al. [1]
  • Risk score imputation from Hsu et al. [2]

Contributor (alphabetical order)

Bartlett, Jonathan (maintainer); Burkoff, Nikolas; Jackson, Dan; Jones, Edmund; Law, Martin; Metcalfe, Paul; Ruau, David;

Installation

To install the development version from GitHub:

install.packages("devtools")
# We spent a lot of time developing the vignettes. We recommend the read but 
# building them from source takes some time
devtools::install_github("jwb133/InformativeCensoring", 
                         build_vignettes = TRUE)

Gamma imputation (Jackson 2014)

The Gamma imputation method implementation was developed in collaboration between AstraZeneca, the MRC Biostatistics Unit and the University of Cambridge.

This implementation was validated to the best of our effort following good coding practice and thorough user testing.

Risk Score Imputation (Hsu 2009)

We implemented the method described in Chiu-Hsieh Hsu and Jeremy Taylor (2009) following the publication.

This implementation was validated to the best of our effort following good coding practice and thorough user testing.

[1] Dan Jackson, Ian White, Shaun Seaman, Hannah Evans, Kathy Baisley, and James Carpenter. Relaxing the independent censoring assumption in the Cox proportional hazards model using multiple imputation. Statistics in Medicine, 33(27):4681–4694, 2014.

[2] Chiu-Hsieh Hsu and Jeremy MG Taylor. Nonparametric comparison of two survival functions with dependent censoring via nonparametric multiple imputation. Statistics in Medicine, 28(3):462–475, 2009.

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Install

install.packages('InformativeCensoring')

Monthly Downloads

257

Version

0.3.6

License

GPL (>= 2) | file LICENSE

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Last Published

June 5th, 2023

Functions in InformativeCensoring (0.3.6)

ScoreImputedData.object

ScoreImputedData object
ScoreStatSet.object

An object which contains the test statistic and estimators for a set of model fits to imputed data using risk score imputation
ScoreTD.object

A ScoreTD object
ScoreStatList.object

ScoreStatList
ScoreImputedSet.object

ScoreImputedSet object
col.headings

Specify the columns of the data frame required by score imputation method
ScoreTimeDep

Simulated time dependent variables for time to event data
ScoreInd

Simulated time to event data with 5 time independent covariates
ScoreStatSet

S3 generic to create a ScoreStatSet object
gammaImpute

Perform gamma-Imputation for a given data set
cox.zph

Test Cox proportional hazards assumption
ScoreStat.object

ScoreStat object
summary.ScoreStatSet

Summary object of ScoreStatSet object
GammaStat.object

GammaStat object
GammaImputedSet.object

GammaImputedSet object
GammaStatList.object

GammaStatList object
ScoreImpute

Perform risk score multiple imputation method
ImputeStat

S3 generic to fit model(s) to risk score/gamma Imputed objects
ExtractSingle

Extract a single risk score/gamma imputed data set/model fit
MakeTimeDepScore

Create a valid ScoreTD object
InformativeCensoring-package

Perform methods of multiple imputation for time to event data
GammaImputedData.object

GammaImputedData object
NN.options

Create a list of options which control the nearest neighbour algorithm for risk score imputation