metaanalyseSmallSampleSizeExperiments

Implements analysis of small sample size experiments based on Hedges and Olkin p128-131.

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

metaanalyseSmallSampleSizeExperiments function

<dl><dt>d</dt>
<dd>a vector of standardized mean differences for different experiments (not adjusted for small sample size)</dd>
<dt>f</dt>
<dd>a vector defining the degrees for each experiment</dd>
<dt>A</dt>
<dd>a vector defining the relationship between d and its related t value for each experiment</dd></dl>

Arguments

Barbara Kitchenham and Lech Madeyski

Author

metaanalyseSmallSampleSizeExperiments — metaanalyseSmallSampleSizeExperiments

<dl>

<dt>d</dt>
<dd>a vector of standardized mean differences for different experiments (not adjusted for small sample size)</dd>


<dt>f</dt>
<dd>a vector defining the degrees for each experiment</dd>


<dt>A</dt>
<dd>a vector defining the relationship between d and its related t value for each experiment</dd>

</dl>

metaanalyseSmallSampleSizeExperiments: metaanalyseSmallSampleSizeExperiments

Description

Usage

Value

Arguments

Author

Examples