test.cor

Computes a t test for a test of the null hypothesis that a population
Pearson or partial correlations is equal to 0, or a z test using a Fisher
transformation for a test of the null hypothesis that a Pearson or
partial correlation is equal to some specified nonzero value. Set s = 0
for a Pearson correlation. The hypothesis testing results should be
accompanied with a confidence interval for the population Pearson or
partial correlation value ((see ci.cor).

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

test.cor function

<dl><dt>cor</dt>
<dd>estimated correlation</dd>
<dt>n</dt>
<dd>sample size</dd>
<dt>s</dt>
<dd>number of control variables</dd>
<dt>h</dt>
<dd>null hypothesis value of correlation</dd></dl>

Arguments

Hypothesis test for a Pearson or partial correlation — test.cor

<dl>

<dt>cor</dt>
<dd>estimated correlation</dd>


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


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


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

</dl>

test.cor: Hypothesis test for a Pearson or partial correlation

Description

Usage

Value

Arguments

Examples