CompC

This function estimates phi function at fixed time point t

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

CompC function

<dl><dt>theta</dt>
<dd>Estimated parameter values/initial values for finite dimensional parameters</dd>
<dt>t</dt>
<dd>A fixed time point</dd>
<dt>X</dt>
<dd>Data matrix with covariates related to T</dd>
<dt>W</dt>
<dd>Data matrix with covariates related to C. First column of W should be ones</dd>
<dt>ld</dt>
<dd>Output of <code>SolveL</code> function at a fixed time t</dd>
<dt>cop</dt>
<dd>Which copula should be computed to account for dependency between T and C. This argument can take
one of the values from <code>c("Gumbel", "Frank", "Normal")</code>. The default copula model is "Frank".</dd>
<dt>dist</dt>
<dd>The distribution to be used for the dependent censoring C. Only two distributions are allowed, i.e, Weibull
and lognormal distributions. With the value <code>"Weibull"</code> as the
 default.</dd></dl>

Arguments

Compute phi function — CompC

<dl>

<dt>theta</dt>
<dd>Estimated parameter values/initial values for finite dimensional parameters</dd>


<dt>t</dt>
<dd>A fixed time point</dd>


<dt>X</dt>
<dd>Data matrix with covariates related to T</dd>


<dt>W</dt>
<dd>Data matrix with covariates related to C. First column of W should be ones</dd>


<dt>ld</dt>
<dd>Output of <code>SolveL</code> function at a fixed time t</dd>


<dt>cop</dt>
<dd>Which copula should be computed to account for dependency between T and C. This argument can take
one of the values from <code>c("Gumbel", "Frank", "Normal")</code>. The default copula model is "Frank".</dd>


<dt>dist</dt>
<dd>The distribution to be used for the dependent censoring C. Only two distributions are allowed, i.e, Weibull
and lognormal distributions. With the value <code>"Weibull"</code> as the
 default.</dd>

</dl>

CompC: Compute phi function

Description

Usage

Arguments