get.cond.moment.evals

This function computes the 1(Y &lt;= t) - Lambda(X^T beta(t)) and
Lambda(X^T beta(t)) - 1(Y &lt;= t, Delta = 1) parts of the moment functions.
(Used in function get.mi.mat.R)

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.cond.moment.evals function

<dl><dt>data</dt>
<dd>Data frame.</dd>
<dt>beta</dt>
<dd>Vector of coefficients.</dd>
<dt>t</dt>
<dd>Time point of interest.</dd>
<dt>hp</dt>
<dd>List of hyperparameters.</dd></dl>

Arguments

Compute the conditional moment evaluations — get.cond.moment.evals

<dl>

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


<dt>beta</dt>
<dd>Vector of coefficients.</dd>


<dt>t</dt>
<dd>Time point of interest.</dd>


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

</dl>

get.cond.moment.evals: Compute the conditional moment evaluations

Description

Usage

Value

Arguments