varStandardizedEffectSize

Function calculates the exact variance of a standardized effect size based on the relationship between t and the standardized effect size, see Morris and DeShon, Combining Effect Size Estimates in Meta-Analysis With Repeated Measures and Independent-Groups Designs, Psychological Methods, 7 (1), pp 105-125.

Includes data analysis and meta-analysis functions (e.g., to
calculate effect sizes and 95% Confidence Intervals (CI) on Standardised
Effect Sizes (d) for AB/BA cross-over repeated-measures experimental
designs), data presentation functions (e.g., density curve overlaid on
histogram),and the data sets analyzed in different research papers in
software engineering (e.g., related to software defect prediction or multi-
site experiment concerning the extent to which structured abstracts were
clearer and more complete than conventional abstracts) to streamline
reproducible research in software engineering.

Lech Madeyski

reproducer

Reproduce Statistical Analyses and Meta-Analyses

Barbara Kitchenham

Tomasz Lewowski

Marian Jureczko

David Budgen

Pearl Brereton

Jacky Keung

Stuart Charters

Shirley Gibbs

Amnart Pohthong

Giuseppe Scanniello

Carmine Gravino

varStandardizedEffectSize function

<dl><dt>d</dt>
<dd>An unadjusted standardized effect size</dd>
<dt>A</dt>
<dd>The squared constant linking t and d i.e. t*sqrt(A)=d</dd>
<dt>f</dt>
<dd>The degrees of freedom of the t value</dd>
<dt>returnVarg</dt>
<dd>if set to TRUE return the variance of the small sample size adjusted standardized effect size (g), otherwise returns var(d) where d is the input parameter</dd></dl>

Arguments

Barbara Kitchenham and Lech Madeyski

Author

varStandardizedEffectSize — varStandardizedEffectSize

<dl>

<dt>d</dt>
<dd>An unadjusted standardized effect size</dd>


<dt>A</dt>
<dd>The squared constant linking t and d i.e. t*sqrt(A)=d</dd>


<dt>f</dt>
<dd>The degrees of freedom of the t value</dd>


<dt>returnVarg</dt>
<dd>if set to TRUE return the variance of the small sample size adjusted standardized effect size (g), otherwise returns var(d) where d is the input parameter</dd>

</dl>

varStandardizedEffectSize: varStandardizedEffectSize

Description

Usage

Value

Arguments

Author

Examples