Logistic Regression Analysis and Reporting: A Primer
- 2 February 2002
- journal article
- Published by Taylor & Francis Ltd in Understanding Statistics
- Vol. 1 (1), 31-70
- https://doi.org/10.1207/s15328031us0101_04
Abstract
Logistic regression, being well suited for analyzing dichotomous outcomes, has been increasingly applied in social science research. That potential expanded usage demands that researchers, editors, and readers be coached in terms of what to expect in an article that used the logistic regression technique: What tables should be included? What assumptions tested? What figures or charts should be expected? In this article we seek to answer these questions with an illustration of logistic regression applied to a real world data set. Results were evaluated and diagnosed in terms of the overall test of the model, interpretability and statistical significance of each predictor, goodness-of-fit statistics, predictive power, accuracy of prediction, and identification of potential outliers. Guidelines are offered for modeling strategies and reporting standards in logistic regression. Furthermore, 6 statistical packages were employed to perform logistic regression. Their strengths and weaknesses were noted in terms ...This publication has 21 references indexed in Scilit:
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