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 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

test.spear function

<dl><dt>cor</dt>
<dd>estimated Spearman 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 Spearman 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