D.hat

This function computes the diagonal matrix of the sample
variance-covariance matrix.

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

D.hat function

<dl><dt>input</dt>
<dd>Can either be the variance-covariance matrix obtained from the
function Sigma.hat, or the data frame.</dd>
<dt>beta</dt>
<dd>The coefficient vector. Only needs to be supplied when the
argument for <code>input</code> is the data frame.</dd>
<dt>t</dt>
<dd>The time point of interest. Only needs to be supplied when the
argument for <code>input</code> is the data frame.</dd>
<dt>hp</dt>
<dd>List of hyperparameters. Only needs to be supplied when the
argument for <code>input</code> is the data frame.</dd>
<dt>m.avg</dt>
<dd>See documentation of <code>Sigma.hat</code>. Only needs to be supplied
when the argument for <code>input</code> is the data frama.</dd>
<dt>mi.mat</dt>
<dd>See documentation of <code>Sigma.hat</code>. Only needs to be supplied
when the argument for <code>input</code> is the data frama.</dd></dl>

Arguments

Obtain the diagonal matrix of sample variances of moment functions — D.hat

<dl>

<dt>input</dt>
<dd>Can either be the variance-covariance matrix obtained from the
function Sigma.hat, or the data frame.</dd>


<dt>beta</dt>
<dd>The coefficient vector. Only needs to be supplied when the
argument for <code>input</code> is the data frame.</dd>


<dt>t</dt>
<dd>The time point of interest. Only needs to be supplied when the
argument for <code>input</code> is the data frame.</dd>


<dt>hp</dt>
<dd>List of hyperparameters. Only needs to be supplied when the
argument for <code>input</code> is the data frame.</dd>


<dt>m.avg</dt>
<dd>See documentation of <code>Sigma.hat</code>. Only needs to be supplied
when the argument for <code>input</code> is the data frama.</dd>


<dt>mi.mat</dt>
<dd>See documentation of <code>Sigma.hat</code>. Only needs to be supplied
when the argument for <code>input</code> is the data frama.</dd>

</dl>

D.hat: Obtain the diagonal matrix of sample variances of moment functions

Description

Usage

Arguments