A Note on the Calculation and Interpretation of the Delta-p Statistic for Categorical Independent Variables
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This methodological note illustrates how a commonly used calculation of the Delta-p statistic is inappropriate for categorical independent variables, and this note provides users of logistic regression with a revised calculation of the Delta-p statistic that is more meaningful when studying the differences in the predicted probability of an outcome between two or more groups. Although one cannot fully document the extent to which this error in the current calculation of the Delta-p statistic has spread across the field, the potential for error is far reaching as an increasing number of researchers use logistic regression to study categorical outcomes and as researchers look more closely at the Delta-p statistic as a means to communicate the results of logistic regression models to policy makers and administrators. It is recommended that higher education scholars and institutional researchers use caution when reporting the Delta-p statistic from prior studies and that they adopt the revised calculation of the Delta-p statistic presented in this methodological note when estimating logistic regression models with categorical independent variables.
KeywordsDelta-p statistic Logistic regression Predictor variables Higher education research Multivariate statistics
I would like to thank J. Scott Long, Thomas F. Nelson Laird, Stephen R. Porter, Robert K. Toutkoushian and two anonymous reviewers for commenting on previous drafts of this manuscript. Any errors are my own.
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