Use of generalised additive models to categorise continuous variables in clinical prediction.

ABSTRACT:

Background

In medical practice many, essentially continuous, clinical parameters tend to be categorised by physicians for ease of decision-making. Indeed, categorisation is a common practice both in medical research and in the development of clinical prediction rules, particularly where the ensuing models are to be applied in daily clinical practice to support clinicians in the decision-making process. Since the number of categories into which a continuous predictor must be categorised depends partly on the relationship between the predictor and the outcome, the need for more than two categories must be borne in mind.

Methods

We propose a categorisation methodology for clinical-prediction models, using Generalised Additive Models (GAMs) with P-spline smoothers to determine t

SUBMITTER: Barrio I 

PROVIDER: S-EPMC3716996 | biostudies-literature | 2013 Jun

REPOSITORIES: biostudies-literature