disattenuate.d

Measurement error (i.e. the complement of reliability) results in a downward bias
of observed effect sizes. This attenuation can be reversed by disattenuation.

This is a new version of the 'userfriendlyscience' package,
which has grown a bit unwieldy. Therefore, distinct functionalities
are being 'consciously uncoupled' into different packages. This package
contains the general-purpose tools and utilities (see the
'behaviorchange' package, the 'rosetta' package, and the
soon-to-be-released 'scd' package for other functionality), and
is the most direct 'successor' of the original 'userfriendlyscience' package.
For example, this package contains a number of basic functions to create
higher level plots, such as diamond plots, to easily plot sampling
distributions, to generate confidence intervals, to plan study sample sizes
for confidence intervals, and to do some basic operations such as
(dis)attenuate effect size estimates.

Gjalt-Jorn Peters

A Collection of Utilities

disattenuate.d function

<dl><dt>d</dt>
<dd>The (attenuated) value of Cohen's d (i.e. the value as observed in the sample,
and therefore attenuated (decreased) by measurement error in the continuous variable).</dd>
<dt>reliability</dt>
<dd>The reliability of the measurements of the continuous variable</dd></dl>

Arguments

Gjalt-Jorn Peters &amp; Stefan Gruijters

Author

Disattenuate a Cohen's d estimate for unreliability in the continuous variable — disattenuate.d

<dl>

<dt>d</dt>
<dd>The (attenuated) value of Cohen's d (i.e. the value as observed in the sample,
and therefore attenuated (decreased) by measurement error in the continuous variable).</dd>


<dt>reliability</dt>
<dd>The reliability of the measurements of the continuous variable</dd>

</dl>

disattenuate.d: Disattenuate a Cohen's d estimate for unreliability in the continuous variable

Description

Usage

Value

Arguments

Author

References

Examples