optimlikelihood

Estimates the model parameters by maximizing the log-likelihood.

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

optimlikelihood function

<dl><dt>Y</dt>
<dd>Follow-up time.</dd>
<dt>Delta</dt>
<dd>Censoring indicator.</dd>
<dt>Copula</dt>
<dd>The copula family. This argument can take values from <code>c("frank","gumbel","clayton","gaussian","indep")</code>.</dd>
<dt>Dist.T</dt>
<dd>The distribution to be used for the survival time T. This argument can take one of the values from <code>c("lnorm", "weibull", "llogis")</code>.</dd>
<dt>Dist.C</dt>
<dd>The distribution to be used for the censoring time C. This argument can take one of the values from <code>c("lnorm", "weibull", "llogis")</code>.</dd>
<dt>start</dt>
<dd>Starting values</dd></dl>

Arguments

Fit the dependent censoring models. — optimlikelihood

<dl>

<dt>Y</dt>
<dd>Follow-up time.</dd>


<dt>Delta</dt>
<dd>Censoring indicator.</dd>


<dt>Copula</dt>
<dd>The copula family. This argument can take values from <code>c("frank","gumbel","clayton","gaussian","indep")</code>.</dd>


<dt>Dist.T</dt>
<dd>The distribution to be used for the survival time T. This argument can take one of the values from <code>c("lnorm", "weibull", "llogis")</code>.</dd>


<dt>Dist.C</dt>
<dd>The distribution to be used for the censoring time C. This argument can take one of the values from <code>c("lnorm", "weibull", "llogis")</code>.</dd>


<dt>start</dt>
<dd>Starting values</dd>

</dl>

optimlikelihood: Fit the dependent censoring models.

Description

Usage

Value

Arguments