lf.ts

This function implements the loss function used in computing
the test statistic.

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

lf.ts function

<dl><dt>beta.sub</dt>
<dd>Subvector of coefficient vector.</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>Unit vector containing unity at the location of the parameter of
interest.</dd>
<dt>r</dt>
<dd>Value of the parameter of interest that is tested.</dd>
<dt>inst.func.evals</dt>
<dd>Pre-computed matrix of insturmental function
evaluations. If not supplied, it will be computed during execution of this
function.</dd></dl>

Arguments

'Loss function' of the test statistic. — lf.ts

<dl>

<dt>beta.sub</dt>
<dd>Subvector of coefficient vector.</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>Unit vector containing unity at the location of the parameter of
interest.</dd>


<dt>r</dt>
<dd>Value of the parameter of interest that is tested.</dd>


<dt>inst.func.evals</dt>
<dd>Pre-computed matrix of insturmental function
evaluations. If not supplied, it will be computed during execution of this
function.</dd>

</dl>

lf.ts: 'Loss function' of the test statistic.

Description

Usage

Value

Arguments