YJtrans

Computes the Yeo-Johnson transformation of the provided argument.

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>
and Willems et al. (2024+) <doi:10.48550/arXiv.2403.11860>.

Negera Wakgari Deresa

depCensoring

Statistical Methods for Survival Data with Dependent Censoring

Ilias Willems

Gilles Crommen

Ingrid Van Keilegom

Claudia Czado

YJtrans function

<dl><dt>y</dt>
<dd>The argument to be supplied to the Yeo-Johnson transformation.</dd>
<dt>theta</dt>
<dd>The parameter of the Yeo-Johnson transformation. This should be
a number in the range [0,2].</dd></dl>

Arguments

Yeo-Johnson transformation function — YJtrans

<dl>

<dt>y</dt>
<dd>The argument to be supplied to the Yeo-Johnson transformation.</dd>


<dt>theta</dt>
<dd>The parameter of the Yeo-Johnson transformation. This should be
a number in the range [0,2].</dd>

</dl>

YJtrans: Yeo-Johnson transformation function

Description

Usage

Value

Arguments