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However, reaction\u2010time distributions are typically right\u2010skewed, complicating statistical analysis and requiring large numbers of repetitions for reliable parameter estimation. One well\u2010known transformation to normalise reaction\u2010time distributions is taking their reciprocal, called \u2018speed\u2019 or \u2018promptness\u2019 (unit 1\/s). Using the promptness transformation for individual visual\u2010field locations typically normalises the corresponding reaction\u2010time distributions and enables more efficient statistical analysis. This study investigated whether pooling promptness across visual\u2010field locations maintains sufficient normality for robust parameter estimation, even with sparse data typical of clinical applications, such as EMP. The results demonstrate that pooled promptness distributions generally retain normal\u2010like properties in normal vision and glaucoma, allowing for efficient estimation of key distribution parameters (mean and standard deviation) with a minimal number of repetitions. These findings suggest that promptness\u2010based metrics could serve as clinically relevant summary indices for visual\u2010function assessment, similar to mean deviation (MD) in standard perimetry. While the reciprocal transformation of reaction time is well established, its targeted application in visual\u2010field analysis via EMP and the robustness to pooling across stimulus conditions, that is, visual\u2010field locations, has not been explored systematically. This study shows that promptness enables compact, interpretable metrics for EMP, even with sparse data. By reducing data collection demands while preserving statistical rigour, this approach offers a promising framework for enhancing the efficiency and applicability of EMP in clinical and research settings.<\/jats:p>","DOI":"10.1111\/opo.13564","type":"journal-article","created":{"date-parts":[[2025,8,8]],"date-time":"2025-08-08T14:44:07Z","timestamp":1754664247000},"page":"2072-2092","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Optimising reaction\u2010time analysis in eye movement perimetry using pooled promptness distributions"],"prefix":"10.1007","volume":"45","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0151-4578","authenticated-orcid":false,"given":"Ashwini Venkat Reddy","family":"Chanakya","sequence":"first","affiliation":[{"name":"Department of Neuroscience Erasmus MC  Rotterdam The Netherlands"},{"name":"Medical Research Foundation, Sankara Nethralaya  Chennai Tamil Nadu 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