Cited by 39Meta-analysis and systematic reviewsSoftware Engineering Techniques and PracticesStatistical Methods in Clinical Trials

Effect sizes and their variance for AB/BA crossover design studies

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Madeyski, Lech, Kitchenham, Barbara·2018·Empirical Software Engineering

Abstract

Vegas et al. IEEE Trans Softw Eng 42(2):120:135 (2016) raised concerns about the use of AB/BA crossover designs in empirical software engineering studies. This paper addresses issues related to calculating standardized effect sizes and their variances that were not addressed by the Vegas et al.’s paper. In a repeated measures design such as an AB/BA crossover design each participant uses each method. There are two major implication of this that have not been discussed in the software engineering literature. Firstly, there are potentially two different standardized mean difference effect sizes that can be calculated, depending on whether the mean difference is standardized by the pooled within groups variance or the within-participants variance. Secondly, as for any estimated parameters and also for the purposes of undertaking meta-analysis, it is necessary to calculate the variance of the standardized mean difference effect sizes (which is not the same as the variance of the study). We present the model underlying the AB/BA crossover design and provide two examples to demonstrate how to construct the two standardized mean difference effect sizes and their variances, both from standard descriptive statistics and from the outputs of statistical software. Finally, we discuss the implication of these issues for reporting and planning software engineering experiments. In particular we consider how researchers should choose between a crossover design or a between groups design.

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Research works printed but not linked: 3

  1. Ciolkowski M (1999) Evaluating the effectiveness of different inspection techniques on informal requirements documents. PhD thesis, University of Kaiserslautern, Kaiserslautern
  2. Hedges LV, Olkin I (1985) Statistical methods for meta-analysis. Academic Press Orlando, Florida
  3. Kitchenham BA, Madeyski L (2016) Meta-analysis. In: Kitchenham B A, Budgen D, Brereton P (eds) Evidence-Based Software Engineering and Systematic Reviews. CRC Press, chap 11, pp 133–154

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Authors
Madeyski, L., & Kitchenham, B.
Affiliations
  • Wrocław University of Science and Technology (PL)
  • Keele University (GB)
Corresponding author
  • Madeyski, Lech
  • Kitchenham, Barbara
Venue
Empirical Software Engineering
Published
2017-12-06
Volume
23
Issue
4
Pages
1982-2017
ISSN
  • 1382-3256 (ISSN-L)
  • 1573-7616
OpenAlex
W2772922594
Cited by
38
References
45
Citations by year
2026: 4 · 2025: 1 · 2024: 5 · 2023: 6 · 2022: 4 · 2021: 5 · 2020: 5 · 2019: 6 · 2018: 2
FWCI
3.20
Type
journal article
Language
en
Open access
Locations
  • Empirical Software Engineering (publishedVersion, cc-by)
  • Keele Research Repository (Keele University) (submittedVersion, cc-by)
Topics
  • Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
  • Physical Sciences › Computer Science › Information Systems › Software Engineering Techniques and Practices
  • Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
Keywords
standardized mean difference, repeated measures designs, meta-analysis, software engineering experiments

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