sGLL

Generalized Log-logistic (GLL) survivor function.

Fits tractable fully parametric odds-based regression models for survival data, including proportional odds (PO), accelerated failure time (AFT), accelerated odds (AO), and General Odds (GO) models in overall survival frameworks. Given at least an R function specifying the survivor, hazard rate and cumulative distribution functions, any user-defined parametric distribution can be fitted. We applied and evaluated a minimum of seventeen (17) various baseline distributions that can handle different failure rate shapes for each of the four different proposed odds-based regression models. For more information see Bennet et al., (1983) <doi:10.1002/sim.4780020223>, and Muse et al., (2022) <doi:10.1016/j.aej.2022.01.033>.

Abdisalam Muse

AmoudSurv

Tractable Parametric Odds-Based Regression Models

Abdisalam Hassan Muse

Samuel Mwalili

Oscar Ngesa

Christophe Chesneau

sGLL function

<dl><dt>t</dt>
<dd>: positive argument</dd>
<dt>kappa</dt>
<dd>: scale parameter</dd>
<dt>alpha</dt>
<dd>: shape parameter</dd>
<dt>eta</dt>
<dd>: shape parameter</dd></dl>

Arguments

Abdisalam Hassan Muse, Samuel Mwalili, Oscar Ngesa, Christophe Chesneau <a href="/link/abdisalam.hassan%40amoud.edu.so?package=AmoudSurv&version=0.1.0" data-mini-rdoc="AmoudSurv::abdisalam.hassan@amoud.edu.so">abdisalam.hassan@amoud.edu.so</a>

Author

Generalized Log-logistic (GLL) survivor function. — sGLL

<dl>

<dt>t</dt>
<dd>: positive argument</dd>


<dt>kappa</dt>
<dd>: scale parameter</dd>


<dt>alpha</dt>
<dd>: shape parameter</dd>


<dt>eta</dt>
<dd>: shape parameter</dd>

</dl>

Abdisalam Hassan Muse, Samuel Mwalili, Oscar Ngesa, Christophe Chesneau <a href='mailto:abdisalam.hassan@amoud.edu.so'>abdisalam.hassan@amoud.edu.so</a>

sGLL: Generalized Log-logistic (GLL) survivor function.

Description

Usage

Value

Arguments

Author

References

Examples