dsndtheta_multneh

Partial derivatives of sn (net survival) by theta for the link_tau="loglinear" model

internal

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

dsndtheta_multneh function

<dl><dt>z_tau</dt>
<dd>Covariates matrix acting on time-to-null parameter.</dd>
<dt>z_alpha</dt>
<dd>Covariates matrix acting on parameter alpha of the density of
time-to-null excess hazard model</dd>
<dt>x</dt>
<dd>time at which the predictions are provided</dd>
<dt>object</dt>
<dd>ouput from a model implemented in curesurv</dd>
<dt>cumLexctopred</dt>
<dd>pre prediction obtained from cumLexc_mul_topred, estimated if NULL</dd>
<dt>Dpi</dt>
<dd>partial derivative of pi according to theta, if NULL will be calculated</dd></dl>

Arguments

Juste Goungounga, Judith Breaud, Olayide Boussari, Laura Botta, Valerie Jooste

Author

dsndtheta_multneh function — dsndtheta_multneh

<dl>

<dt>z_tau</dt>
<dd>Covariates matrix acting on time-to-null parameter.</dd>


<dt>z_alpha</dt>
<dd>Covariates matrix acting on parameter alpha of the density of
time-to-null excess hazard model</dd>


<dt>x</dt>
<dd>time at which the predictions are provided</dd>


<dt>object</dt>
<dd>ouput from a model implemented in curesurv</dd>


<dt>cumLexctopred</dt>
<dd>pre prediction obtained from cumLexc_mul_topred, estimated if NULL</dd>


<dt>Dpi</dt>
<dd>partial derivative of pi according to theta, if NULL will be calculated</dd>

</dl>

dsndtheta_multneh: dsndtheta_multneh function

Description

Usage

Arguments

Author

References