Structured PREreview of "Female Signatories and Peace Durability: Replicating Krause, Krause, and Bränfors (2018)"

Abstract

This Zenodo record is a permanently preserved version of a Structured PREreview. You can view the complete PREreview at https://prereview.org/reviews/23431625. Does the introduction explain the objective of the research presented in the preprint? Yes The introduction clearly explains the research objectives. It states that the study aims to replicate the quantitative analysis of Krause, Krause, and Bränfors (2018), assess the reproducibility of their findings, and examine potential limitations concerning statistical power and model specification. Are the methods well-suited for this research? Somewhat appropriate The replication approach is suitable for the research, as the authors reproduce the original Cox proportional hazards models and robustness tests. However, the methodological assessment has some gaps. In particular, the power analysis reports values of 0.44 and 0.99 without providing the formula, software procedure, or sufficient calculation details to allow readers to reproduce the estimates. The choice of 42 events in Table 6 also needs clarification, given that Table 5 reports 54 events overall. Additionally, the differences between the original and reproduced sample sizes remain unexplained. These issues weaken the transparency and reproducibility of the analysis. Are the conclusions supported by the data? Somewhat supported The main conclusion is that the original findings can be reproduced, which is supported by the reported results. The authors also reasonably identify the small number of female-signatory agreements and the limitations of drawing causal conclusions from the observed association. However, the claim that the analysis has low statistical power relies on a calculation for which the formula and detailed procedure are not provided (Table 6). The differences between the original and reproduced sample sizes also remain unexplained. These limitations make some aspects of the interpretation less conclusive than they could be. Are the data presentations, including visualizations, well-suited to represent the data? Somewhat appropriate and clear The survival analysis and regression tables are suitable for presenting the findings. However, some numerical inconsistencies in the descriptive statistics and differences in sample sizes across the original and reproduced models need clarification to ensure the results are presented accurately. For instance, Table 3 presents: three major statistical flaws: 1: Conflict Intensity row, where Female Signatories = 1: has SD of 1.2 while the Max is 0.45, which is statistically incorrect. Similarly, (2) Democracy row where Female Signatories = 1, has Mean 0.92 < Min 1. And lastly, on page 5, UN peacekeeping is written as a binary number, however, in Table 3, the binary UN Peacekeeping has Max > 1. All these minor inconsistencies require clarification. How clearly do the authors discuss, explain, and interpret their findings and potential next steps for the research? Very clearly The authors explain their findings, acknowledge the limitations of the small number of agreements with female signatories, and discuss the implications for causal interpretation. They also identify the need for further research, although the power analysis and differences in sample sizes could be explained more transparently. Is the preprint likely to advance academic knowledge? Somewhat likely If the author clarified the sample-size discrepancies and documented the power analysis more transparently, then it would substantially contribute to the reproducibility of an influential finding, as it already highlights the reproducibility of the findings and highlights the limitations in statistical power and causal interpretation. Would it benefit from language editing? No The languages is clear and no major errors could be found hinderig the understanding of the resarch. However some minor issues could be corrected, such as, constant capitalisation of the first letter in column names. Would you recommend this preprint to others? Yes, but it needs to be improved The preprint offers a useful contribution to replication research and raises important questions about statistical power and causal interpretation. However, the authors should clarify the power analysis and sample-size discrepancies to strengthen the paper's reliability. Is it ready for attention from an editor, publisher or broader audience? Yes, after minor changes The preprint addresses a relevant academic question and offers a useful replication analysis. Before wider dissemination, the author should clarify the power analysis and sample-size discrepancies and ensure that the statistical results are presented consistently. Competing interests The author declares that they have no competing interests. Use of Artificial Intelligence (AI) The author declares that they did not use generative AI to come up with new ideas for their review.