Estimable Functions in Log-Linear Models
J. Scott Long
Additional contact information
J. Scott Long: Washington State University
Sociological Methods & Research, 1984, vol. 12, issue 4, 399-432
Abstract:
Since Goodman's introduction of log-linear models to social scientists in 1972, the technique has become a basic tool. Applications have been limited, however, by a serious misunderstanding of the interpretation of parameters in log-linear models. The problem arises from attempts to interpret the parameters as though they are similar to regression coefficients, rather than as similar to ANOVA coefficients. More technically, the problem arises from a failure to understand the concept of estimability and its application to log-linear analysis. This article defines the concept of estimability for log-linear models, indicates the implications of this concept for the interpretation of parameters in log-linear models, and provides rules for determining the estimability of linear functions of parameters.
Date: 1984
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
https://journals.sagepub.com/doi/10.1177/0049124184012004004 (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:12:y:1984:i:4:p:399-432
DOI: 10.1177/0049124184012004004
Access Statistics for this article
More articles in Sociological Methods & Research
Bibliographic data for series maintained by SAGE Publications ().