Titlebook: Validity, Reliability, and Significance; Empirical Methods fo Stefan Riezler,Michael Hagmann Book 2024Latest edition The Editor(s) (if appl

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Reliability,her hand, in the pursuit of high reliability, validity tends to get lost, for example, by oversimplifying measurement procedures or by overly strict annotation instructions. More often than not, the notion of reliability is claimed as the primary criterion for the adequacy of a measurement. However,

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Significance,stical significance testing is often completely ignored. The goal of this chapter is to promote model-based significance testing using LMEMs, and to revitalize the generalized likelihood ratio test (GLRT) as a hypothesis test framework that shows its full potential in a model-based setting. GLRTs da

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Stefan Riezler,Michael HagmannIncludes problems of validity, reliability, and significance and provides solutions based on statistical methodology.introduces empirical methods for machine learning with a focus on applications in N

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https://doi.org/10.1007/978-3-031-57065-0Empirical Methods; Validity; Generalized Additive Models; Deviance; Reliability; Orthogonal Estimators; Si