A Comparison of Log-Linear and Regression Models for Systems of Dichotomous Variables

David Knoke
Additional contact information
David Knoke: Indiana University

Sociological Methods & Research, 1975, vol. 3, issue 4, 416-434

Abstract: The relative abilities of dummy variable regression and log-linear models to locate significant relationships in systems of dichotomous variables are compared. On logical grounds log-linear models are superior to regression since the data more readily meet the assumptions of the former. Two illustrative examples suggest that the methods converge in their findings when the range in proportions of the dependent dichotomy is between .25 and. 75, but may differ on which effects are significant when proportions are more extreme. Substantive differences under the two methods are likely to be small, however.

Date: 1975
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://journals.sagepub.com/doi/10.1177/004912417500300403 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:sae:somere:v:3:y:1975:i:4:p:416-434

DOI: 10.1177/004912417500300403

Access Statistics for this article

More articles in Sociological Methods & Research
Bibliographic data for series maintained by SAGE Publications ().