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Sample Size Impact on the Categorisation of Continuous Variables in Clinical Prediction

Name: Sample Size Impact on the Categorisation of Continuous Variables in Clinical Prediction
Keywords: categorisation, sample size

descriptionPublicationkeyboard_double_arrow_right Part of book or chapter of book 01 Jan 2017Publisher:Springer International Publishing

Authors: Barrio, I.; Arostegui, I.; Rodríguez-Álvarez, M.X.;

doi: 10.1007/978-3-319-55639-0_3

handle: 20.500.11824/773

Sample Size Impact on the Categorisation of Continuous Variables in Clinical Prediction

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Abstract

Recent advances in information technologies are generating a growth in the amount of available biomedical data. In this paper, we studied the impact sample size may have on the categorisation of a continuous predictor variable in a logistic regression setting. Two different approaches to categorise predictor variables were compared.

MINECO: MTM2011-28285-C02-01, MTM2013-40941-P, MTM2014-55966-P. Basque Government: IT620-13. University of the Basque Country UPV/EHU: UFI11/52 Agrupamento INBIOMED from DXPCTSUG-FEDER unha maneira de facer Europa (2012/273).

Related Organizations

University of the Basque Country
Spain
Universidade de Vigo
Spain
Basque Center for Applied Mathematics
Spain

Keywords

categorisation, sample size

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