convert_d_r

convert_r_d

Invertible conversions between a two-group standardized mean difference
(Cohen's d) and the (point-biserial) correlation between the
outcome and group membership. <code>convert_d_r()</code> maps d to
r; <code>convert_r_d()</code> maps r back to d. These are
the standard conversions used to bring effect sizes reported in different
metrics onto a common scale, for example when synthesizing a literature in
which some studies report mean differences and others report correlations
(Borenstein, Hedges, Higgins, &amp; Rothstein, 2009, Chapter 7).

design

Methods for design, measurement, and analysis, with the
aim of being user friendly yet methodologically sound. 'DMAR' (pronounced "Dee-Mar") implements
many advanced and nonstandard methods and makes them available for
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methodological literature, in support of sound and reproducible
results. The package
emphasizes effect size estimation with confidence intervals;
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whose conclusions require several results to hold at once), with
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with confidence intervals to measurement invariance; factor
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Measurement is approached from a psychometric perspective, and
although many of the methods grew up in human-centered research,
they apply broadly across the empirical sciences.
Much of what is implemented traces to the author's methodological
work, interests, and collaborations. 'DMAR' is a more modern, more general,
and greatly expanded reimagining of the 'MBESS' package (Kelley,
2007a, <doi:10.18637/jss.v020.i08>; 2007b,
<doi:10.3758/BF03192993>), which has been on CRAN for more than
two decades and remains available there in stable form. Most functions accept either
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and planning functions return one consistently formatted data
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throughout, as best practice recommends. Researchers who have data
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approachable, while methodologists gain access to advanced and
nonstandard methods, including tables of critical values not
available elsewhere.

Ken Kelley

DMAR

Design, Measurement, and Analysis in R (DMAR)

convert_d_r function

<dl><dt>d</dt>
<dd>The standardized mean difference.</dd>
<dt>n_1, n_2</dt>
<dd>Optional per-group sample sizes. When supplied, the
conversion uses the unequal-group factor
\(a = (n_1 + n_2)^2 / (n_1 n_2)\); when omitted, equal group sizes are
assumed, for which \(a = 4\).</dd>
<dt>r</dt>
<dd>The point-biserial correlation, in \((-1, 1)\).</dd></dl>

Arguments

Ken Kelley <a href="/link/kkelley%40nd.edu?package=DMAR&version=1.0.0" data-mini-rdoc="DMAR::kkelley@nd.edu">kkelley@nd.edu</a>

Author

Convert Between the Standardized Mean Difference and the Correlation — convert_d_r

<dl>

<dt>d</dt>
<dd>The standardized mean difference.</dd>


<dt>n_1, n_2</dt>
<dd>Optional per-group sample sizes. When supplied, the
conversion uses the unequal-group factor
\(a = (n_1 + n_2)^2 / (n_1 n_2)\); when omitted, equal group sizes are
assumed, for which \(a = 4\).</dd>


<dt>r</dt>
<dd>The point-biserial correlation, in \((-1, 1)\).</dd>

</dl>

Ken Kelley <a href='mailto:kkelley@nd.edu'>kkelley@nd.edu</a>

convert_d_r: Convert Between the Standardized Mean Difference and the Correlation

Description

Usage

Value

Arguments

Author

Details

References

See Also

Examples