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The Analysis of Relationships Involving Dichotomous Dependent Variables

Paul D. Cleary and Ronald Angel
Journal of Health and Social Behavior
Vol. 25, No. 3 (Sep., 1984), pp. 334-348
Stable URL: http://www.jstor.org/stable/2136429
Page Count: 15
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The Analysis of Relationships Involving Dichotomous Dependent Variables
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Abstract

Several methods of modeling dichotomous dependent variables are reviewed from both theoretical and practical points of view. We conclude that logistic or probit models are the more theoretically appropriate, but that there are often insignificant practical differences between the results of logistic regression, discriminant analysis, and linear probability functions. Discriminant analysis and linear regression are recommended for exploratory analysis if local software limitations make them more accessible or less expensive than logistic regression programs; logistic analysis is recommended for more exact model fitting and hypothesis testing.

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