pmodavg

Obtains the distribution function value for model-averaging
of Weibull and log-normal regression.

internal

Predicts enrollment and events at the design or analysis stage
using specified enrollment and time-to-event models through
simulations.

Kaifeng Lu

eventPred

Event Prediction

pmodavg function

<dl><dt>t</dt>
<dd>The vector of time points.</dd>
<dt>theta</dt>
<dd>The parameter vector consisting of the accelerate failure
time (AFT) regression coefficients and the logrithm of the AFT
regression scale parameter for the Weibull and log-normal distributions.</dd>
<dt>w1</dt>
<dd>The weight for the Weibull component distribution.</dd>
<dt>q</dt>
<dd>The number of elements in the vector of covariates
(excluding the intercept).</dd>
<dt>x</dt>
<dd>The vector of covariates (including the intercept).</dd>
<dt>lower.tail</dt>
<dd>logical; if TRUE (default), probabilities are
the distribution function, otherwise, the survival function.</dd>
<dt>log.p</dt>
<dd>logical; if TRUE, probabilities p are given as log(p).</dd></dl>

Arguments

Distribution function for model averaging of Weibull and log-normal — pmodavg

<dl>

<dt>t</dt>
<dd>The vector of time points.</dd>


<dt>theta</dt>
<dd>The parameter vector consisting of the accelerate failure
time (AFT) regression coefficients and the logrithm of the AFT
regression scale parameter for the Weibull and log-normal distributions.</dd>


<dt>w1</dt>
<dd>The weight for the Weibull component distribution.</dd>


<dt>q</dt>
<dd>The number of elements in the vector of covariates
(excluding the intercept).</dd>


<dt>x</dt>
<dd>The vector of covariates (including the intercept).</dd>


<dt>lower.tail</dt>
<dd>logical; if TRUE (default), probabilities are
the distribution function, otherwise, the survival function.</dd>


<dt>log.p</dt>
<dd>logical; if TRUE, probabilities p are given as log(p).</dd>

</dl>

pmodavg: Distribution function for model averaging of Weibull and log-normal

Description

Usage

Value

Arguments