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• W3136126986 abstract "Clinical trials often aim to compare two groups of patients for efficacy and/or toxicity depending on covariates such as dose. Examples include the comparison of populations from different geographic regions or age classes or, alternatively, of different treatment groups. Similarity of these groups can be claimed if the difference in average outcome is below a certain margin over the entire covariate range. In this article, we consider the problem of testing for similarity in the case that efficacy and toxicity are measured as binary outcome variables. We develop a new test for the assessment of similarity of two groups for a single binary endpoint. Our approach is based on estimating the maximal deviation between the curves describing the responses of the two groups, followed by a parametric bootstrap test. Further, using a two-dimensional Gumbel-type model we develop methodology to establish similarity for (correlated) binary efficacy-toxicity outcomes. We investigate the operating characteristics of the proposed methodology by means of a simulation study and present a case study as an illustration." @default.
• W3136126986 created "2021-03-29" @default.
• W3136126986 creator A5051037589 @default.
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• W3136126986 date "2021-03-19" @default.
• W3136126986 modified "2023-10-18" @default.
• W3136126986 title "Testing for similarity of binary efficacy–toxicity responses" @default.
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• W3136126986 doi "https://doi.org/10.1093/biostatistics/kxaa058" @default.
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• W3136126986 hasPublicationYear "2021" @default.
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