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 |
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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 | |
Publication status | Published - 2019 |