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The use of logistic discrimination and receiver operating characteristics (ROC) analysis in dentistry


Helfenstein, Ulrich; Steiner, Marcel (1994). The use of logistic discrimination and receiver operating characteristics (ROC) analysis in dentistry. Community Dental Health, 11(3):142-146.

Abstract

Logistic regression is a statistical method which allows an investigator to 'explain' or 'predict' a binary response variable from a set of independent variables. In particular, it may be used to classify persons for example, as diseased or healthy, high risk or low risk etc. (logistic discrimination). During recent years this method has been of increasing interest and importance in dentistry. Since this demanding statistical method may not be easily accessible to dentists, a description is provided of its basic characteristics in an introductory and condensed form. A worked example, 'identification of children with high caries risk', is presented in order to demonstrate the application and use of the method. Following the presentation of the logistic model, evaluation of the performance of a classification model by means of 'receiver operating characteristic (ROC) analysis' is demonstrated. The presentation of these statistical tools here, puts more weight on verbal explanation and on graphical representations than on mathematical details. This statistical tools here, puts more weight on verbal explanation and on graphical representations than on mathematical details. This may help to make the methods accessible to readers who have insufficient time to study a more comprehensive discourse.

Abstract

Logistic regression is a statistical method which allows an investigator to 'explain' or 'predict' a binary response variable from a set of independent variables. In particular, it may be used to classify persons for example, as diseased or healthy, high risk or low risk etc. (logistic discrimination). During recent years this method has been of increasing interest and importance in dentistry. Since this demanding statistical method may not be easily accessible to dentists, a description is provided of its basic characteristics in an introductory and condensed form. A worked example, 'identification of children with high caries risk', is presented in order to demonstrate the application and use of the method. Following the presentation of the logistic model, evaluation of the performance of a classification model by means of 'receiver operating characteristic (ROC) analysis' is demonstrated. The presentation of these statistical tools here, puts more weight on verbal explanation and on graphical representations than on mathematical details. This statistical tools here, puts more weight on verbal explanation and on graphical representations than on mathematical details. This may help to make the methods accessible to readers who have insufficient time to study a more comprehensive discourse.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > Epidemiology, Biostatistics and Prevention Institute (EBPI)
Dewey Decimal Classification:610 Medicine & health
Language:English
Date:September 1994
Deposited On:10 Jun 2016 14:41
Last Modified:08 Dec 2017 19:41
Publisher:FDI World Dental Press
ISSN:0265-539X
PubMed ID:7953932

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