Package: depCensoring 0.1.3

depCensoring: Statistical Methods for Survival Data with Dependent Censoring

Several statistical methods for analyzing survival data under various forms of dependent censoring are implemented in the package. In addition to accounting for dependent censoring, it offers tools to adjust for unmeasured confounding factors. The implemented approaches allow users to estimate the dependency between survival time and dependent censoring time, based solely on observed survival data. For more details on the methods, refer to Deresa and Van Keilegom (2021) <doi:10.1093/biomet/asaa095>, Czado and Van Keilegom (2023) <doi:10.1093/biomet/asac067>, Crommen et al. (2024) <doi:10.1007/s11749-023-00903-9> and Willems et al. (2024+) <doi:10.48550/arXiv.2403.11860>.

Authors:Ilias Willems [aut], Gilles Crommen [aut], Negera Wakgari Deresa [aut, cre], Ingrid Van Keilegom [aut], Claudia Czado [aut]

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depCensoring.pdf |depCensoring.html✨
depCensoring/json (API)
NEWS

# Install 'depCensoring' in R:
install.packages('depCensoring', repos = c('https://nago2020.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/nago2020/depcensoring/issues

On CRAN:

2.70 score 5 scripts 275 downloads 5 exports 47 dependencies

Last updated 1 months agofrom:786a9741d1. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 16 2024
R-4.5-winOKNov 16 2024
R-4.5-linuxOKNov 16 2024
R-4.4-winOKNov 16 2024
R-4.4-macOKNov 16 2024
R-4.3-winOKNov 16 2024
R-4.3-macOKNov 16 2024

Exports:estimate.cmprskNonParTransParamCopSolveHTCsim

Dependencies:ADGofTestassertthatBHclicodetoolscolorspacecopuladigestdoParallelforeachgluegsliteratorskde1dlatticelifecyclemagrittrMASSMatrixmatrixcalcmvtnormnleqslvnloptrnumDerivOpenMxpbivnormpcaPPpsplinerafalibrandtoolboxRColorBrewerRcppRcppEigenRcppParallelRcppThreadrlangrngWELLrpfrvinecopulibSemiPar.depCensstabledistStanHeadersstringistringrsurvivalvctrswdm

Readme and manuals

Help Manual

Help pageTopics
Nonparametric bootstrap approach for a Semiparametric transformation model under dependent censpringboot.nonparTrans
Compute bivariate survival probabilityBvprob
Transform Cholesky decomposition to covariance matrixchol2par
Transform Cholesky decomposition to covariance matrix parameter element.chol2par.elem
Competing risk likelihood function.cr.lik
Data generation function for competing risks datadat.sim.reg.comp.risks
Derivative of transform Cholesky decomposition to covariance matrix.dchol2par
Derivative of transform Cholesky decomposition to covariance matrix element.dchol2par.elem
Distance between vectorsDistance
Derivative of the Yeo-Johnson transformation functionDYJtrans
Estimate the control functionestimate.cf
Estimate the competing risks model of Rutten, Willems et al. (20XX).estimate.cmprsk
Inverse Yeo-Johnson transformation functionIYJtrans
Second step log-likelihood function.LikF.cmprsk
Wrapper implementing likelihood function using Cholesky factorization.likF.cmprsk.Cholesky
First step log-likelihood function for Z continuousLikGamma1
First step log-likelihood function for Z binary.LikGamma2
Second likelihood function needed to fit the independence model in the second step of the estimation procedure.LikI.bis
Second step log-likelihood function under independence assumption.LikI.cmprsk
Wrapper implementing likelihood function assuming independence between competing risks and censoring using Cholesky factorization.LikI.cmprsk.Cholesky
Full likelihood (including estimation of control function).likIFG.cmprsk.Cholesky
Logarithmic transformation function.log_transform
Log-likelihood function for the Clayton copula.loglike.clayton.unconstrained
Log-likelihood function for the Frank copula.loglike.frank.unconstrained
Log-likelihood function for the Gaussian copula.loglike.gaussian.unconstrained
Log-likelihood function for the Gumbel copula.loglike.gumbel.unconstrained
Log-likelihood function for the independence copula.loglike.indep.unconstrained
Change H to long formatLongfun
Fit a semiparametric transformation model for dependent censoringNonParTrans
Fit the dependent censoring models.optimlikelihood
Estimation of a parametric dependent censoring model without covariates.ParamCop
Power transformation function.power_transform
Score equations of finite parametersScoreEqn
Search functionSearchIndicate
Estimate a nonparametric transformation functionSolveH
Estimating equation for Ht1SolveHt1
Estimate finite parameters based on score equationsSolveScore
Function to simulate (Y,Delta) from the copula based model for (T,C).TCsim
Standardize data formatuniformize.data
Compute the variance of the estimates.variance.cmprsk
Yeo-Johnson transformation functionYJtrans