depcorr1

Compute Power for Comparing Two Dependent Correlations, One Variable in Common
Takes correlations and range of values

Statistical power analysis for designs including t-tests, correlations,
multiple regression, ANOVA, mediation, and logistic regression. Functions accompany
Aberson (2019) <doi:10.4324/9781315171500>.

Chris Aberson

pwr2ppl

Power Analyses for Common Designs (Power to the People)

depcorr1 function

<dl><dt>r1y</dt>
<dd>Correlation between the first predictor and the dependent variable</dd>
<dt>r2y</dt>
<dd>Correlation between the second predictor and the dependent variable</dd>
<dt>r12</dt>
<dd>Correlation between the first predictor and the second predictor</dd>
<dt>nlow</dt>
<dd>Starting sample size</dd>
<dt>nhigh</dt>
<dd>Ending sample size</dd>
<dt>alpha</dt>
<dd>Type I error (default is .05)</dd>
<dt>tails</dt>
<dd>one or two-tailed tests (default is 2)</dd>
<dt>by</dt>
<dd>Incremental increase in sample size from low to high</dd></dl>

Arguments

Compute Power for Comparing Two Dependent Correlations, One Variable in Common
Takes correlations and range of values — depcorr1

<dl>

<dt>r1y</dt>
<dd>Correlation between the first predictor and the dependent variable</dd>


<dt>r2y</dt>
<dd>Correlation between the second predictor and the dependent variable</dd>


<dt>r12</dt>
<dd>Correlation between the first predictor and the second predictor</dd>


<dt>nlow</dt>
<dd>Starting sample size</dd>


<dt>nhigh</dt>
<dd>Ending sample size</dd>


<dt>alpha</dt>
<dd>Type I error (default is .05)</dd>


<dt>tails</dt>
<dd>one or two-tailed tests (default is 2)</dd>


<dt>by</dt>
<dd>Incremental increase in sample size from low to high</dd>

</dl>

depcorr1: Compute Power for Comparing Two Dependent Correlations, One Variable in Common Takes correlations and range of values

Description

Usage

Value

Arguments

Examples