test.spear

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

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.spear function

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

Arguments

Hypothesis test for a Spearman correlation — test.spear

<dl>

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


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


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

</dl>

test.spear: Hypothesis test for a Spearman correlation

Description

Usage

Value

Arguments

Examples