Preparing Data for Predictive Modelling

Sander van Kuijk; Frank Dankers; Alberto Traverso; Leonard Wee

doi:10.1007/978-3-319-99713-1_6

Preparing Data for Predictive Modelling

Sander van Kuijk^*, Frank Dankers, Alberto Traverso, Leonard Wee

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Chapter › Academic

Abstract

This is the first chapter of five that cover an introduction to developing and validating models for predicting outcomes for the individual patient. Such prediction models can be used for predicting the occurrence or recurrence of an event, or of the most likely value on a continuous outcome. We will mainly focus on the prediction of binary outcomes, such as the occurrence of a complication, recurrence of disease, the presence of metastases, remission, survival, etc. This chapter deals with the selection of an appropriate study design for a study on prediction, and on methods to manipulate the data before the statistical modelling can begin.

Original language	English
Title of host publication	Fundamentals of Clinical Data Science
Editors	Pieters Kubben, Michel Dumontier, Andre Dekker
Publisher	Springer
Chapter	6
Pages	75-84
Number of pages	10
ISBN (Electronic)	978-3-319-99713-1
ISBN (Print)	978-3-319-99712-4
DOIs	https://doi.org/10.1007/978-3-319-99713-1_6
Publication status	Published - 2019

Access to Document

10.1007/978-3-319-99713-1_6Licence: CC BY

Cite this

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