sploglog

Split-population Log-logistic regression

internal

An implementation of split-population duration regression models.
Unlike regular duration models, split-population duration models are
mixture models that accommodate the presence of a sub-population that is
not at risk for failure, e.g. cancer patients who have been cured by
treatment. This package implements Weibull and Loglogistic forms for the
duration component, and focuses on data with time-varying covariates.
These models were originally formulated in Boag (1949) and Berkson and Gage
(1952), and extended in Schmidt and Witte (1989).

Andreas Beger

spduration

Split-Population Duration (Cure) Regression

Daina Chiba

Daniel W. Hill, Jr.

Nils W. Metternich

Shahryar Minhas

Michael D. Ward

sploglog function

<dl><dt>Y</dt>
<dd>Dependent variables.</dd>
<dt>X</dt>
<dd>Duration equation covariates.</dd>
<dt>Z</dt>
<dd>Risk equation covariates.</dd>
<dt>max.iter</dt>
<dd>Maximum iterations to try.</dd>
<dt>silent</dt>
<dd>Suppress <code><a href="/link/optim?package=spduration&version=0.17.2" data-mini-rdoc="spduration::optim">optim</a></code> trace output?</dd></dl>

Arguments

Split-population Log-logistic regression — sploglog

<dl>

<dt>Y</dt>
<dd>Dependent variables.</dd>


<dt>X</dt>
<dd>Duration equation covariates.</dd>


<dt>Z</dt>
<dd>Risk equation covariates.</dd>


<dt>max.iter</dt>
<dd>Maximum iterations to try.</dd>


<dt>silent</dt>
<dd>Suppress <code><a href='https://rdrr.io/r/stats/optim.html'>optim</a></code> trace output?</dd>

</dl>

sploglog: Split-population Log-logistic regression

Description

Usage

Arguments