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

You Answered:

Selection AStill be unbiased estimates.

INCORRECT

When modeling decisions are based on the data under study, bias is introduced. The correct answer is: (c) Be biased to more extreme values. When modeling decisions are based on the data under study, we usually pick up more extreme patterns than present in the underlying population. Hence, p-values are estimated too small, and regression coefficients too large (in absolute value). Regression to the mean may be expected when the model is validated in new patients.

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