Two.Prop.Test.Sample.Size

Calculates the required sample size for a two-group comparison of
proportions based on the method of Casagrande, Pike, and Smith (1978).

Implements Bayesian hybrid designs that incorporate historical
control data into a current clinical trial. The package uses a dynamic
power prior method to determine the degree of borrowing from the historical
data, creating a 'hybrid' control arm. This approach is primarily
designed for studies with a binary primary endpoint, such as the overall
response rate (ORR). Functions are provided for design calibration,
sample size calculation, power evaluation, and final analysis.
Additionally, it includes functions adapted from the 'SAMprior' package
(v1.1.1) by Yang et al. (2023) <https://academic.oup.com/biometrics/article/79/4/2857/7587575> to support the
Self-Adapting Mixture (SAM) prior framework for comparison.

Zhaohua Lu

BayesianHybridDesign

Bayesian Hybrid Design and Analysis

Philip He

Two.Prop.Test.Sample.Size function

<dl><dt>p1</dt>
<dd>A scalar. The anticipated proportion in Arm 1 (e.g., control).</dd>
<dt>p2</dt>
<dd>A scalar. The anticipated proportion in Arm 2 (e.g., experimental).</dd>
<dt>alpha</dt>
<dd>A scalar. The one-sided Type I error rate.</dd>
<dt>beta</dt>
<dd>A scalar. The Type II error rate (1 - power).</dd>
<dt>r</dt>
<dd>A scalar. The randomization ratio of Arm 2 to Arm 1 ($n_2/n_1$).</dd></dl>

Arguments

Sample Size for Comparing Two Proportions — Two.Prop.Test.Sample.Size

<dl>

<dt>p1</dt>
<dd>A scalar. The anticipated proportion in Arm 1 (e.g., control).</dd>


<dt>p2</dt>
<dd>A scalar. The anticipated proportion in Arm 2 (e.g., experimental).</dd>


<dt>alpha</dt>
<dd>A scalar. The one-sided Type I error rate.</dd>


<dt>beta</dt>
<dd>A scalar. The Type II error rate (1 - power).</dd>


<dt>r</dt>
<dd>A scalar. The randomization ratio of Arm 2 to Arm 1 ($n_2/n_1$).</dd>

</dl>

Two.Prop.Test.Sample.Size: Sample Size for Comparing Two Proportions

Description

Usage

Value

Arguments

See Also

Examples