spearmanbrown

Computes the reliability of a scale that is the sum or average of r2
parallel measurements given the reliability of a scale that is the sum or
average of r1 parallel measurements. The "measurements" can be items,
trials, raters, or occasions.

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

spearmanbrown function

<dl><dt>rel</dt>
<dd>reliability of the sum or average of r1 measurements</dd>
<dt>r1</dt>
<dd>number of measurements in the original scale</dd>
<dt>r2</dt>
<dd>number of measurements in the new scale</dd></dl>

Arguments

Computes the reliability of a scale with r2 measurements given the
reliability of a scale with r1 measurements — spearmanbrown

<dl>

<dt>rel</dt>
<dd>reliability of the sum or average of r1 measurements</dd>


<dt>r1</dt>
<dd>number of measurements in the original scale</dd>


<dt>r2</dt>
<dd>number of measurements in the new scale</dd>

</dl>

spearmanbrown: Computes the reliability of a scale with r2 measurements given the reliability of a scale with r1 measurements

Description

Usage

Value

Arguments

Examples