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Statistical Models for Prognostication
Author Bio
Introduction
Predictions: Statistical Models
Insight: Statistical Models
Ingredients: Statistical Models
Theoretical Aspects
Central Concepts
Currently selected section: Regression Models
Problems: Regression
Practical Advice
Example 1
Example 2
Chapter 8: Statistical Models for Prognostication: Development of Regression Models
        

You Answered:

Selection ABecause of collinearity, a choice has to be made between one of the correlated variables.

INCORRECT

Collinearity is usually no problem for predictive purposes. The correct answer is (c), correlated variables may well be combined to obtain a more stable measurement of the underlying biological phenomenon. An example is taking the mean of diastolic and systolic blood pressure. Related variables may also be combined in a summary variable. For example, an atherosclerotic risk variable may be created based on the presence of various signs that indicate atherosclerosis (Krijnen et al., 1998). Also, we might count the number of signs to form such a variable (Harrell et al., 1985).

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