rGenGamma

Generates generalized gamma event times with shape parameters
\((\alpha,\beta)\), and rate parameter \(\lambda\). See
<code>FitGenGamma</code> for the parameterization. If a censoring
proportion \(p\) is provided, the event times are subject to
non-informative random right censoring.

Performs maximum likelihood based estimation and inference on time to event data, possibly subject to non-informative right censoring. FitParaSurv() provides maximum likelihood estimates of model parameters and distributional characteristics, including the mean, median, variance, and restricted mean. CompParaSurv() compares the mean, median, and restricted mean survival experiences of two treatment groups. Candidate distributions include the exponential, gamma, generalized gamma, log-normal, and Weibull.

Zachary McCaw

Temporal

Parametric Time to Event Analysis

rGenGamma function

<dl><dt>n</dt>
<dd>Sample size.</dd>
<dt>a</dt>
<dd>First shape parameter, \(\alpha\).</dd>
<dt>b</dt>
<dd>Second shape parameter, \(\beta\). For the standard gamma
distribution, set \(\beta=1\).</dd>
<dt>l</dt>
<dd>Rate.</dd>
<dt>p</dt>
<dd>Expected censoring proportion.</dd></dl>

Arguments

Simulation from the Generalized Gamma Distribution — rGenGamma

<dl>

<dt>n</dt>
<dd>Sample size.</dd>


<dt>a</dt>
<dd>First shape parameter, \(\alpha\).</dd>


<dt>b</dt>
<dd>Second shape parameter, \(\beta\). For the standard gamma
distribution, set \(\beta=1\).</dd>


<dt>l</dt>
<dd>Rate.</dd>


<dt>p</dt>
<dd>Expected censoring proportion.</dd>

</dl>

rGenGamma: Simulation from the Generalized Gamma Distribution

Description

Usage

Value

Arguments