loglike.gaussian.unconstrained

This likelihood function is maximized to estimate the model parameters under the Gaussian copula.

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

loglike.gaussian.unconstrained function

<dl><dt>para</dt>
<dd>Estimated parameter values/initial values.</dd>
<dt>Y</dt>
<dd>Follow-up time.</dd>
<dt>Delta</dt>
<dd>Censoring indicator.</dd>
<dt>Dist.T</dt>
<dd>The distribution to be used for the survival time T. This argument can only the value <code>"lnorm"</code>.</dd>
<dt>Dist.C</dt>
<dd>The distribution to be used for the censoring time C. This argument can only the value <code>"lnorm"</code>.</dd></dl>

Arguments

Log-likelihood function for the Gaussian copula. — loglike.gaussian.unconstrained

<dl>

<dt>para</dt>
<dd>Estimated parameter values/initial values.</dd>


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


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


<dt>Dist.T</dt>
<dd>The distribution to be used for the survival time T. This argument can only the value <code>"lnorm"</code>.</dd>


<dt>Dist.C</dt>
<dd>The distribution to be used for the censoring time C. This argument can only the value <code>"lnorm"</code>.</dd>

</dl>

loglike.gaussian.unconstrained: Log-likelihood function for the Gaussian copula.

Description

Usage

Value

Arguments