A Simple and Transparent Alternative to Logistic Regression
DOI:
https://doi.org/10.14738/assrj.37.2125Abstract
Observation oriented modeling was compared to logistic regression in the re-analysis of data from a published study. In the original study students’ decisions to stop or continue controversial animal research was predicted from gender, the type of research being conducted, and measures of ethical attitudes. With regard to classification accuracy, results from the observation oriented modeling analyses compared favorably to results obtained from logistic regression and two other methods of classification. Prediction profiles created from the observation oriented modeling analyses were moreover parsimonious and transparent, and the analyses themselves were free of assumptions. Unique features of the observation oriented modeling approach were discussed.Downloads
Published
2016-07-30
How to Cite
Grice, J. W., Cota, L. D., Barrett, P. T., Wuensch, K. L., & Poteat, M. (2016). A Simple and Transparent Alternative to Logistic Regression. Advances in Social Sciences Research Journal, 3(7). https://doi.org/10.14738/assrj.37.2125
Issue
Section
Articles
License
Authors wishing to include figures, tables, or text passages that have already been published elsewhere are required to obtain permission from the copyright owner(s) for both the print and online format and to include evidence that such permission has been granted when submitting their papers. Any material received without such evidence will be assumed to originate from the authors.