testiscancer

Simulated dataset of 2000 individuals as in Boussari et al. (2020),
following setting 1 sub-scenario design.

datasets

Fits a variety of cure models using excess hazard modeling methodology such as the mixture model proposed by Phillips et al. (2002) <doi:10.1002/sim.1101> The Weibull distribution is used to represent the survival function of the uncured patients; Fits also non-mixture cure model such as the time-to-null excess hazard model proposed by Boussari et al. (2020) <doi:10.1111/biom.13361>.

Juste Goungounga

curesurv

Mixture and Non Mixture Parametric Cure Models to Estimate Cure
Indicators

Judith Breaud

Olayide Boussari

Laura Botta 

Valerie Jooste

testiscancer function

This dataset contains the following variables:<dl>
<dt>age</dt>
<dd>Age at diagnosis</dd><dt>age_cr</dt>
<dd>centered and scaled age at diagnosis</dd><dt>age_classe</dt>
<dd>"&lt;40", "40_65" and "&gt;=65" age groups</dd><dt>time_obs</dt>
<dd>Follow-up time (years)</dd><dt>event</dt>
<dd>Vital status</dd><dt>cumehazard</dt>
<dd>individual cumulative expected hazard</dd><dt>ehazard</dt>
<dd>individual instantaneous expected hazard</dd><dt>weisurvpop</dt>
<dd>individual expected survival</dd>
</dl>

Format

Simulated testis cancer data using a cure model — testiscancer

This dataset contains the following variables:<dl>
<dt>age</dt>
<dd>Age at diagnosis</dd>

<dt>age_cr</dt>
<dd>centered and scaled age at diagnosis</dd>

<dt>age_classe</dt>
<dd>"&lt;40", "40_65" and "&gt;=65" age groups</dd>

<dt>time_obs</dt>
<dd>Follow-up time (years)</dd>

<dt>event</dt>
<dd>Vital status</dd>

<dt>cumehazard</dt>
<dd>individual cumulative expected hazard</dd>

<dt>ehazard</dt>
<dd>individual instantaneous expected hazard</dd>

<dt>weisurvpop</dt>
<dd>individual expected survival</dd>


</dl>

testiscancer: Simulated testis cancer data using a cure model

Description

Usage

Arguments

Format

Examples