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Optimal Scaling: Discretization

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Machine Learning in Medicine

Abstract

In clinical trials the research question is often measured with multiple variables, and multiple regression is commonly used for analysis. The problem with multiple regression is that consecutive levels of the variables are assumed to be equal, while in practice this is virtually never true. Optimal scaling is a method designed to maximize the relationship between a predictor and an outcome variable by adjusting their scales.

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Authors and Affiliations

Authors

Appendix: Datafile of 250 Subjects Used as Example

Appendix: Datafile of 250 Subjects Used as Example

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  1. G gene, O outcome

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Cleophas, T.J., Zwinderman, A.H. (2013). Optimal Scaling: Discretization. In: Machine Learning in Medicine. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-5824-7_3

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