cormean

This function computes a minimally biased average of correlation values.
This is needed because simple averaging of correlations is negatively biased,
and the often used z-transformation method of averaging correlations is positively biased.
The algorithm was developed by Olkin &amp; Pratt (1958).

Compute approach bias scores using different scoring algorithms,
compute bootstrapped and exact split-half reliability estimates,
and compute confidence intervals for individual participant scores.

Sercan Kahveci

AATtools

Reliability and Scoring Routines for the Approach-Avoidance Task

cormean function

<dl><dt>r</dt>
<dd>a vector containing correlation values</dd>
<dt>n</dt>
<dd>a single value or vector containing sample sizes</dd>
<dt>wts</dt>
<dd>Character. How should the correlations be weighted?
<code>none</code> leads to no weighting, <code>n</code> weights by sample size, <code>df</code> weights by sample size minus one.</dd>
<dt>type</dt>
<dd>Character. Determines which averaging algorithm to use, with "OP5" being the most accurate.</dd>
<dt>na.rm</dt>
<dd>Logical. Should missing values be removed?</dd></dl>

Arguments

Compute a minimally biased average of correlation values — cormean

<dl>

<dt>r</dt>
<dd>a vector containing correlation values</dd>


<dt>n</dt>
<dd>a single value or vector containing sample sizes</dd>


<dt>wts</dt>
<dd>Character. How should the correlations be weighted?
<code>none</code> leads to no weighting, <code>n</code> weights by sample size, <code>df</code> weights by sample size minus one.</dd>


<dt>type</dt>
<dd>Character. Determines which averaging algorithm to use, with "OP5" being the most accurate.</dd>


<dt>na.rm</dt>
<dd>Logical. Should missing values be removed?</dd>

</dl>

cormean: Compute a minimally biased average of correlation values

Description

Usage

Value

Arguments

References

Examples