Visually Enhanced Python Functions for Clinical Equality of Measurement Assessment
Mauro Nascimben, Lia Rimondini
Citation: Communication Papers of the 17th Conference on Computer Science and Intelligence Systems, M. Ganzha, L. Maciaszek, M. Paprzycki, D. Ślęzak (eds). ACSIS, Vol. 32, pages 241–249 (2022)
Abstract. Equivalence testing requires specific procedures usually provided by specialized statistical software. The proposed package includes customized methods to assess biomedical equivalence and focuses on translating the outcomes into visual reports. The functions are coded in an object-oriented framework, contain improved plots or novel graphs to facilitate interpretation of the results, and are accompanied by console textual outputs to support users with additional explanations. Special attention has been devoted to verifying the preliminary assumptions of the statistical tests with automatic routines. The current module covers four aspects of biomedical statistics (equivalence, Bland--Altman and ROC analyses, effect size, and confidence intervals interpretation), offering these methodologies to the biomedical community as accessible stand-alone functions. The manuscript defines software's functions and innovations with examples and theoretical explanations.
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