cophfunc

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>, Rutten et al. (2024+)
<doi:10.48550/arXiv.2403.11860> and Ding and Van Keilegom (2024).

Negera Wakgari Deresa

depCensoring

Statistical Methods for Survival Data with Dependent Censoring

Ilias Willems

Gilles Crommen

Jie Ding

Claudia Czado

Ingrid Van Keilegom

cophfunc function

<dl><dt>x</dt>
<dd>the value at which the h-function will be calculated at.</dd>
<dt>coppar</dt>
<dd>a numeric value that denotes the copula parameter.</dd>
<dt>copfam</dt>
<dd>a character string that denotes the copula family.</dd>
<dt>condvar</dt>
<dd>a numeric value that specifies the type of the h-function.</dd></dl>

Arguments

The h-function of the copula — cophfunc

<dl>

<dt>x</dt>
<dd>the value at which the h-function will be calculated at.</dd>


<dt>coppar</dt>
<dd>a numeric value that denotes the copula parameter.</dd>


<dt>copfam</dt>
<dd>a character string that denotes the copula family.</dd>


<dt>condvar</dt>
<dd>a numeric value that specifies the type of the h-function.</dd>

</dl>

The h-function of the copula

cophfunc: The h-function of the copula

Description

Usage

Arguments