CensRate.OneArm

Calculate the censoring rate for a one-arm design

Predict the course of clinical trial with a time-to-event endpoint for both two-arm and single-arm design. Each of the four primary study design parameters (the expected number of observed events, the number of subjects enrolled, the observation time, and the censoring parameter) can be derived analytically given the other three parameters. And the simulation datasets can be generated based on the design settings.

Yang Ding

ClinTrialPredict

Predicting and Simulating Clinical Trial with Time-to-Event
Endpoint

CensRate.OneArm function

<dl><dt>N</dt>
<dd>Number of subjects plan to enrolled</dd>
<dt>d</dt>
<dd>expected number of events observed at time <code>l</code></dd>
<dt>s</dt>
<dd>enrollment period</dd>
<dt>m</dt>
<dd>maximum follow-up for a single subject</dd>
<dt>l</dt>
<dd>observation time</dd>
<dt>alpha</dt>
<dd>shape parameter of weibull survival distribution</dd>
<dt>nu</dt>
<dd>scale parameter of weibull survival distribution</dd></dl>

Arguments

Calculate the censoring rate for a one-arm design — CensRate.OneArm

<dl>

<dt>N</dt>
<dd>Number of subjects plan to enrolled</dd>


<dt>d</dt>
<dd>expected number of events observed at time <code>l</code></dd>


<dt>s</dt>
<dd>enrollment period</dd>


<dt>m</dt>
<dd>maximum follow-up for a single subject</dd>


<dt>l</dt>
<dd>observation time</dd>


<dt>alpha</dt>
<dd>shape parameter of weibull survival distribution</dd>


<dt>nu</dt>
<dd>scale parameter of weibull survival distribution</dd>

</dl>

CensRate.OneArm: Calculate the censoring rate for a one-arm design

Description

Usage

Value

Arguments

Examples