find2stageThetaF

Finds maximum conditional power at which trial will stop for futility

Finds single- and two-arm designs using stochastic curtailment, as described by Law et al. (2022) <doi:10.1080/10543406.2021.2009498> and Law et al. (2021) <doi:10.1002/pst.2067> respectively. Designs can be single-stage or multi-stage. Non-stochastic curtailment is possible as a special case. Desired error-rates, maximum sample size and lower and upper anticipated response rates are inputted and suitable designs are returned with operating characteristics. Stopping boundaries and visualisations are also available. The package can find designs using other approaches, for example designs by Simon (1989) <doi:10.1016/0197-2456(89)90015-9> and Mander and Thompson (2010) <doi:10.1016/j.cct.2010.07.008>. Other features: compare and visualise designs using a weighted sum of expected sample sizes under the null and alternative hypotheses and maximum sample size; visualise any binary outcome design.

Martin Law

curtailment

Finds Binary Outcome Designs Using Stochastic Curtailment

find2stageThetaF function

<dl><dt>r</dt>
<dd>Number of responses to be exceeded for trial success</dd>
<dt>r1</dt>
<dd>Number of responses to be exceeded to continue to second stage</dd>
<dt>n2</dt>
<dd>Sample size of second stage</dd>
<dt>p</dt>
<dd>Response rate under alternative hypothesis H1</dd></dl>

Arguments

Find conditional power for futility — find2stageThetaF

<dl>

<dt>r</dt>
<dd>Number of responses to be exceeded for trial success</dd>


<dt>r1</dt>
<dd>Number of responses to be exceeded to continue to second stage</dd>


<dt>n2</dt>
<dd>Sample size of second stage</dd>


<dt>p</dt>
<dd>Response rate under alternative hypothesis H1</dd>

</dl>

find2stageThetaF: Find conditional power for futility

Description

Usage

Value

Arguments

Examples