Abstract
In elucidating risk factors, or attempting to make predictions about the behavior
of subjects in our biomedical studies, we often build statistical models. These models
are meant to capture some aspect of reality, or some real-world process underlying
the phenomena we are examining. However, no model is perfect, and it is thus important
to have tools to assess how accurate models are. In this commentary, we delve into
the various roles that our models can play. Then we introduce the notion of the goodness
of fit of models and lay the ground work for further study of diagnostic tests for
assessing both the fidelity of our models and the statistical assumptions underlying
them.
Keywords
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References
- Investigators' corner: assumptions of statistical tests: what lies beneath.J Foot Ankle Surg. 2017; 56: 910-913
- Investigators' corner: logistic models—an odd(s) kind of regression.J Foot Ankle Surg. 2013; 52: 279-280
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- Investigators' corner: assessing diagnostic tests II: grading on a curve.J Foot Ankle Surg. 2015; 54: 765-766
- Investigators' corner: random effects: variance is the spice of life.J Foot Ankle Surg. 2016; 55: 1343-1346
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Article info
Footnotes
Financial Disclosure: None reported.
Conflict of Interest: None reported.
Identification
Copyright
© 2017 by the American College of Foot and Ankle Surgeons. All rights reserved.
