llik_pwexp

Obtains the log likelihood value for piecewise
exponential 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

llik_pwexp function

<dl><dt>theta</dt>
<dd>The parameter vector consisting of gamma for log
piecewise hazards and beta for regression coefficients.</dd>
<dt>time</dt>
<dd>The survival time.</dd>
<dt>event</dt>
<dd>The event indicator.</dd>
<dt>J</dt>
<dd>The number of time intervals.</dd>
<dt>tcut</dt>
<dd>A vector that specifies the endpoints of time intervals
for the baseline piecewise exponential survival distribution.
Must start with 0, e.g., c(0, 60) breaks the time axis into 2 event
intervals: [0, 60) and [60, Inf). By default, it is set to 0.</dd>
<dt>q</dt>
<dd>The number of columns of the covariates matrix.</dd>
<dt>x</dt>
<dd>The covariates matrix (excluding the intercept).</dd></dl>

Arguments

Log likelihood for piecewise exponential regression — llik_pwexp

<dl>

<dt>theta</dt>
<dd>The parameter vector consisting of gamma for log
piecewise hazards and beta for regression coefficients.</dd>


<dt>time</dt>
<dd>The survival time.</dd>


<dt>event</dt>
<dd>The event indicator.</dd>


<dt>J</dt>
<dd>The number of time intervals.</dd>


<dt>tcut</dt>
<dd>A vector that specifies the endpoints of time intervals
for the baseline piecewise exponential survival distribution.
Must start with 0, e.g., c(0, 60) breaks the time axis into 2 event
intervals: [0, 60) and [60, Inf). By default, it is set to 0.</dd>


<dt>q</dt>
<dd>The number of columns of the covariates matrix.</dd>


<dt>x</dt>
<dd>The covariates matrix (excluding the intercept).</dd>

</dl>

llik_pwexp: Log likelihood for piecewise exponential regression

Description

Usage

Value

Arguments