get.cvLLn

This function computes the critical value following the
algorithm of Section 4.3 in Bei (2024).

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

get.cvLLn function

<dl><dt>BetaI.r</dt>
<dd>Matrix containing in its columns the minimizers of the
S-function leading to the test statistic.</dd>
<dt>data</dt>
<dd>Data frame.</dd>
<dt>t</dt>
<dd>Time point of interest. Also allowed to
be a vector of time points (used in estimating the model under assumed time-
independent coefficients).</dd>
<dt>hp</dt>
<dd>List of hyperparameters.</dd>
<dt>c</dt>
<dd>Projection vector.</dd>
<dt>r</dt>
<dd>Result of projection of parameter vector onto <code>c</code>.</dd>
<dt>par.space</dt>
<dd>Bounds on the parameter space.</dd>
<dt>inst.func.evals</dt>
<dd>Matrix of precomputed instrumental function
evaluations for each observation in the data set. If <code>NULL</code>, the
evaluations will be computed during execution of this function. Default is
<code>inst.func.evals = NULL</code>.</dd>
<dt>alpha</dt>
<dd>Confidence level.</dd></dl>

Arguments

Compute the critical value of the test statistic. — get.cvLLn

<dl>

<dt>BetaI.r</dt>
<dd>Matrix containing in its columns the minimizers of the
S-function leading to the test statistic.</dd>


<dt>data</dt>
<dd>Data frame.</dd>


<dt>t</dt>
<dd>Time point of interest. Also allowed to
be a vector of time points (used in estimating the model under assumed time-
independent coefficients).</dd>


<dt>hp</dt>
<dd>List of hyperparameters.</dd>


<dt>c</dt>
<dd>Projection vector.</dd>


<dt>r</dt>
<dd>Result of projection of parameter vector onto <code>c</code>.</dd>


<dt>par.space</dt>
<dd>Bounds on the parameter space.</dd>


<dt>inst.func.evals</dt>
<dd>Matrix of precomputed instrumental function
evaluations for each observation in the data set. If <code>NULL</code>, the
evaluations will be computed during execution of this function. Default is
<code>inst.func.evals = NULL</code>.</dd>


<dt>alpha</dt>
<dd>Confidence level.</dd>

</dl>

get.cvLLn: Compute the critical value of the test statistic.

Description

Usage

Value

Arguments

References