size.test.cor

Computes the sample size required to test a population Pearson or a partial
correlation with desired power. Set s = 0 for a Pearson correlation.
For more details, see Section 1.25 of Bonett (2021, Volume 2)

Implements confidence interval and sample size methods that are especially
useful in psychological research but are also useful in educational, social science,
business, and biological research. This package includes more than 100 confidence
interval functions and more than 80 sample size functions for 1-group, 2-group,
paired-samples, and multiple-group designs and for a variety of parameters including
means, medians, proportions, slopes, standardized mean differences, standardized
linear contrasts of means, and several measures of correlation and association. 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 about these methods 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

size.test.cor function

<dl><dt>alpha</dt>
<dd>alpha level for hypothesis test</dd>
<dt>pow</dt>
<dd>desired power</dd>
<dt>cor</dt>
<dd>planning value of correlation</dd>
<dt>s</dt>
<dd>number of control variables</dd>
<dt>h</dt>
<dd>null hypothesis value of correlation</dd></dl>

Arguments

Sample size for a test of a Pearson or partial correlation — size.test.cor

<dl>

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


<dt>pow</dt>
<dd>desired power</dd>


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


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


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

</dl>

size.test.cor: Sample size for a test of a Pearson or partial correlation

Description

Usage

Value

Arguments

References

Examples