Statistical Methods for Survival Data with Dependent Censoring
Nonparametric bootstrap approach for a Semiparametric transformation m...
Compute bivariate survival probability
Chronometer object
Prepare initial values within the control arguments
The distribution function of the Archimedean copula
The h-function of the copula
Convert the copula parameter the Kendall's tau
Distance between vectors
Estimate the competing risks model of Willems et al. (2025).
Fit Dependent Censoring Models
Fit Independent Censoring Models
The generator function of the Archimedean copula
Calculate the kernel function
Convert the Kendall's tau into the copula parameter
Calculate the likelihood function for the fully parametric joint distr...
Calculate the profiled likelihood function with kernel smoothing
Solve the profiled likelihood function
Calculate the semiparametric version of profiled likelihood function
Log-likelihood function for the Clayton copula.
Log-likelihood function for the Frank copula.
Log-likelihood function for the Gaussian copula.
Log-likelihood function for the Gumbel copula.
Log-likelihood function for the independence copula.
Change H to long format
Fit a semiparametric transformation model for dependent censoring
Fit the dependent censoring models.
Obtain the value of the density function
Obtain the value of the distribution function
Obtain the adjustment value of truncation
Estimation of a parametric dependent censoring model without covariate...
Generate constraints of parameters
Estimate the model of Willems et al. (2025).
Estimate the model of D'Haen et al. (2025).
Score equations of finite parameters
Search function
Estimate a nonparametric transformation function
Estimating equation for Ht1
Cumulative hazard function of survival time under dependent censoring
Cumulative hazard function of survival time under independent censorin...
Estimate finite parameters based on score equations
Summary of depCensoringFit object
Summary of indepCensoringFit object
Calculate the goodness-of-fit test statistic
Semiparametric Estimation of the Survival Function under Dependent Cen...
Estimated survival function based on copula-graphic estimator (Archime...
Estimated survival function based on Kaplan-Meier estimator
Likelihood for a given parametric distribution
Maximum likelihood estimator for a given parametric distribution
Function to simulate (Y,Delta) from the copula based model for (T,C).
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>, Deresa and Van Keilegom (2024) <doi:10.1080/01621459.2022.2161387>, Willems et al. (2025) <doi:10.48550/arXiv.2403.11860>, Ding and Van Keilegom (2025) and D'Haen et al. (2025) <doi:10.1007/s10985-025-09647-0>.