power.cor

Computes the approximate power of a test for a population Pearson or partial
correlation test for a planned sample size. Set s = 0 for a Pearson correlation.

Implements confidence interval and sample size methods that
are especially useful in psychological research. The methods can be
applied in 1-group, 2-group, paired-samples, and multiple-group designs
and to a variety of parameters including means, medians, proportions,
slopes, standardized mean differences, standardized linear contrasts
of means, plus several measures of correlation and association.
Confidence interval and sample size functions are given for single
parameters as well as differences, ratios, and linear contrasts of
parameters. The sample size functions can be used to approximate the
sample size needed to estimate a parameter or function of parameters
with desired confidence interval precision or to perform a variety of
hypothesis tests (directional two-sided, equivalence, superiority,
noninferiority) with desired power. For details see: Statistical Methods
for Psychologists, Volumes 1 – 4, <https://dgbonett.sites.ucsc.edu/>.

Douglas G. Bonett

statpsych

Statistical Methods for Psychologists

Robert J. Calin-Jageman

power.cor function

<dl><dt>alpha</dt>
<dd>alpha level for hypothesis test</dd>
<dt>n</dt>
<dd>planned sample size</dd>
<dt>cor</dt>
<dd>planning value of correlation</dd>
<dt>h</dt>
<dd>null hypothesis value of correlation</dd>
<dt>s</dt>
<dd>number of control variables</dd></dl>

Arguments

Approximates the power of a correlation test for a planned sample size — power.cor

<dl>

<dt>alpha</dt>
<dd>alpha level for hypothesis test</dd>


<dt>n</dt>
<dd>planned sample size</dd>


<dt>cor</dt>
<dd>planning value of correlation</dd>


<dt>h</dt>
<dd>null hypothesis value of correlation</dd>


<dt>s</dt>
<dd>number of control variables</dd>

</dl>

power.cor: Approximates the power of a correlation test for a planned sample size

Description

Usage

Value

Arguments

Examples