cbMV

This function combines a list of individual identified intervals
to a single one based on majority vote. Note that the intersection of all
intervals can be viewed as a majority vote as well, so that it is included as
a special case.

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

cbMV function

<dl><dt>results.list</dt>
<dd>List object containing the individual identified
intervals.</dd>
<dt>threshold</dt>
<dd>Threshold proportion of identified intervals a given value
should be contained in in order for it to be included in the combined
identified interval. For intersection bounds, set this value to <code>1</code>.</dd></dl>

Arguments

Combine bounds based on majority vote. — cbMV

<dl>

<dt>results.list</dt>
<dd>List object containing the individual identified
intervals.</dd>


<dt>threshold</dt>
<dd>Threshold proportion of identified intervals a given value
should be contained in in order for it to be included in the combined
identified interval. For intersection bounds, set this value to <code>1</code>.</dd>

</dl>

cbMV: Combine bounds based on majority vote.

Description

Usage

Value

Arguments