proportionOfSignificantTValuesUsingCorrectAnalysis

Plots visualize the relationship between sample size, effect size and the proportion of significant t-values using the correct analysis. Function is used in a paper 'Effect Sizes and their Variance for AB/BA Crossover Design Studies' by Lech Madeyski and Barbara Kitchenham.

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

proportionOfSignificantTValuesUsingCorrectAnalysis function

<dl><dt>data</dt>
<dd>- data behind the plot returned by getSimulatedCrossoverDataSets() or stored in reproducer::KitchenhamMadeyski.SimulatedCrossoverDataSets</dd></dl>

Arguments

Barbara Kitchenham and Lech Madeyski

Author

proportionOfSignificantTValuesUsingCorrectAnalysis — proportionOfSignificantTValuesUsingCorrectAnalysis

<dl>

<dt>data</dt>
<dd>- data behind the plot returned by getSimulatedCrossoverDataSets() or stored in reproducer::KitchenhamMadeyski.SimulatedCrossoverDataSets</dd>

</dl>

proportionOfSignificantTValuesUsingCorrectAnalysis: proportionOfSignificantTValuesUsingCorrectAnalysis

Description

Usage

Value

Arguments

Author

Examples