Nomographic representation of logistic regression models: a case study using patient self-assessment data |
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Authors: | Dreiseitl Stephan Harbauer Alexandra Binder Michael Kittler Harald |
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Affiliation: | Department of Software Engineering, University of Applied Sciences, Upper Austria at Hagenberg, Austria. Stephan.Dreiseitl@fh-hagenberg.at |
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Abstract: | Logistic regression models are widely used in medicine, but difficult to apply without the aid of electronic devices. In this paper, we present a novel approach to represent logistic regression models as nomograms that can be evaluated by simple line drawings. As a case study, we show how data obtained from a questionnaire-based patient self-assessment study on the risks of developing melanoma can be used to first identify a subset of significant covariates, build a logistic regression model, and finally transform the model to a graphical format. The advantage of the nomogram is that it can easily be mass-produced, distributed and evaluated, while providing the same information as the logistic regression model it represents. |
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