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Article
Kitchenham, BA
ORCID: https://orcid.org/0000-0002-6134-8460, Madeyski, L and Budgen, D
(2023)
SEGRESS: Software Engineering Guidelines for REporting Secondary Studies.
IEEE Transactions on Software Engineering, 49 (3).
1273 - 1298.
Kitchenham, BA
ORCID: https://orcid.org/0000-0002-6134-8460, Madeyski, L and Budgen, D
(2023)
How Should Software Engineering Secondary Studies Include Grey Material?
IEEE Transactions on Software Engineering, 49 (2).
872 - 882.
Kitchenham, BA
ORCID: https://orcid.org/0000-0002-6134-8460, Madeyski, L, Scanniello, G and Gravino, C
(2022)
The Importance of the Correlation in Crossover Experiments.
IEEE Transactions on Software Engineering, 48 (8).
2802 - 2813.
Madeyski, L, Lewowski, T and Kitchenham, BA
ORCID: https://orcid.org/0000-0002-6134-8460
(2021)
OECD Recommendation's draft concerning access to research data from public funding: A review.
Bulletin of the Polish Academy of Sciences Technical Sciences, 69 (1).
Kitchenham, BA
ORCID: https://orcid.org/0000-0002-6134-8460 and Madeyski, L
(2020)
Inconsistencies with formulas for the standard error of the standardized mean difference of repeated measures experiments.
Statistics in Medicine, 39 (27).
4101 - 4104.
Kitchenham, B, Madeyski, L and Brereton, P (2019) Meta-analysis for families of experiments in software engineering: a systematic review and reproducibility and validity assessment. Empirical Software Engineering.
Kitchenham, BA, Madeyski, L and Curtin, F (2017) Corrections to effect size variances for continuous outcomes of cross-over clinical trials. Statistics in Medicine, 37 (2).
Madeyski, L and Kitchenham, BA (2017) Effect sizes and their variance for AB/BA crossover design studies. EMPIRICAL SOFTWARE ENGINEERING, 23 (4). 1982 - 2017.
Madeyski, L and Kitchenham, BA (2017) Would wider adoption of reproducible research be beneficial for empirical software engineering research? Journal of Intelligent and Fuzzy Systems, 32 (2). pp. 1509-1521.
Brereton, OP, Kitchenham, BA, Madeyski, L, Budgen, D, Keung, J, Charters, S, Gibbs, S and Pohthong, A (2016) Robust Statistical Methods for Empirical Software Engineering. Empirical Software Engineering: an international journal, 22 (2). 579- 630.
Book Section
Kitchenham, BA, Madeyski, L and Brereton, OP (2019) Problems with Statistical Practice in Software Engineering Research. In: EASE '19 Proceedings of the Evaluation and Assessment on Software Engineering. ACM, pp. 134-143.

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