hazard

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

hazard function

<dl><dt>ti</dt>
<dd>Vector of duration values over which to evaluate the hazard function.</dd>
<dt>lambda</dt>
<dd>density function parameter</dd>
<dt>cure</dt>
<dd>density function parameter</dd>
<dt>alpha</dt>
<dd>density function parameter</dd>
<dt>out</dt>
<dd>not used</dd>
<dt>dist</dt>
<dd>"weibull" or "loglog"</dd></dl>

Arguments

Calculate hazard function values — hazard

<dl>

<dt>ti</dt>
<dd>Vector of duration values over which to evaluate the hazard function.</dd>


<dt>lambda</dt>
<dd>density function parameter</dd>


<dt>cure</dt>
<dd>density function parameter</dd>


<dt>alpha</dt>
<dd>density function parameter</dd>


<dt>out</dt>
<dd>not used</dd>


<dt>dist</dt>
<dd>"weibull" or "loglog"</dd>

</dl>

Calculate hazard function values

hazard: Calculate hazard function values

Description

Usage

Arguments