NotesFAQContact Us
Collection
Advanced
Search Tips
Back to results
Peer reviewed Peer reviewed
Direct linkDirect link
ERIC Number: EJ1306321
Record Type: Journal
Publication Date: 2021
Pages: 21
Abstractor: As Provided
ISBN: N/A
ISSN: ISSN-0022-0973
EISSN: N/A
Available Date: N/A
Making the Cut: Comparing Methods for Selecting Cut-Point Location in Logistic Regression
Weiss, Brandi A.; Dardick, William
Journal of Experimental Education, v89 n4 p721-741 2021
Classification measures and entropy variants can be used as indicators of model fit for logistic regression. These measures rely on a cut-point, "c," to determine predicted group membership. While recommendations exist for determining the location of the cut-point, these methods are primarily anecdotal. The current study used Monte Carlo simulation to compare misclassification rates and entropy variants across four cut-point selection methods: default 0.5, MAXCC, nonevent rate, and MAXSS. Minimal differences were found between methods when group sizes were equal or large between-groups differences were present. The MAXSS method was invariant to group size ratios, however, yielded the highest total misclassification rate and highest amount of misfit. The 0.5 and MAXCC methods are recommended for use in applied research. Recommendations are provided for researchers concerned with small group classification who may use the MAXSS method. "EFR" and "EFR-rescaled" were less influenced by cut-point location than classification methods.
Routledge. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals
Publication Type: Journal Articles; Reports - Research
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Grant or Contract Numbers: N/A
Author Affiliations: N/A