LikGamma2

This function defines the maximum likelihood used to estimate
the control function in the case of a binary endogenous variable.

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

LikGamma2 function

<dl><dt>gamma</dt>
<dd>Vector of coefficients in the logistic model used to estimate
the control function.</dd>
<dt>Z</dt>
<dd>Endogenous covariate.</dd>
<dt>M</dt>
<dd>Design matrix, containing an intercept, the exogenous covariates and
the instrumental variable.</dd></dl>

Arguments

First step log-likelihood function for Z binary. — LikGamma2

<dl>

<dt>gamma</dt>
<dd>Vector of coefficients in the logistic model used to estimate
the control function.</dd>


<dt>Z</dt>
<dd>Endogenous covariate.</dd>


<dt>M</dt>
<dd>Design matrix, containing an intercept, the exogenous covariates and
the instrumental variable.</dd>

</dl>

LikGamma2: First step log-likelihood function for Z binary.

Description

Usage

Value

Arguments