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

Predictors

Predictor variables are characteristics associated with the patient. For example, common predictor variables might include:

  • Demographics (age, sex)
  • Symptoms (e.g. pain, dyspnea)
  • Risk factors at presentation (e.g. related to the severity of disease)
  • History characteristics (e.g. related to previous disease course), and
  • Comorbidity (presence of other disease or diseases).
Statistically speaking, predictors are the independent variables X in a prediction problem. We also refer to predictors as "covariables."

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