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Discriminant analysis – simplified

Sandhya Jain, Merin Kuriakose

Abstract


Background: Discriminant function analysis is the statistical analysis used to analyze data when the dependent variable or outcome is categorical and independent variable or predictor variable is parametric. Discriminant function analysis is used to find out the accuracy of a given classification system or predictor variable in predicting the sample into a particular group. Discriminant function analysis includes the development of discriminant functions for each sample and deriving a cutoff score. The cutoff score is used for classifying the samples into different groups. Aim: The aim of this review article is to simplify and explain the discriminant function analysis so that it can be used by medical and dental researchers whenever it is applicable. Conclusion: Discriminant function analysis is a statistical analysis used to find out the accuracy of a given classification system or predictor variables. This paper explains the basics of discriminant analysis and how to interpret the results along with one simple example of mandibular canine index for gender identification. Clinical significance: Whenever a new classification system is introduced or any predictor variable is identified, discriminant function analysis can be used to find out the accuracy with which the classification system or predictor variable can differentiate a sample into different groups. Thus, it is a very useful tool in dental and medical research.

Keywords


Assumptions; data analysis; dependent variable; discriminant function analysis; independent variable; prediction; standard coefficient

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References


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