A recent recommendation by Holt that coefficients resulting from estimating
log-linear and similar models should not be interpreted is argued to be based on
lack of clarity about the substantive and theoretical importance of the choice
between dummy and effect coding for categorical variables. As a consequence,
his recommendation applies only when the main concern is for a balance between
parsimony and goodness of fit to the data and is inappropriate when interest lies
in correct specification of a model representing the substantive process generating
the data.
Get full access to this article
View all access options for this article.
References
1.
Cohen, J. and P. Cohen (1975) Applied Multiple Regression/Correlation Analysis for the Behavioral SciencesHillsdale, NJ: Erlbaum.
Goldberger, A.S. (1973) "Structural equation models: an overview," pp. 1-18 A. S. Goldberger and O. D. Duncan (eds.) Structural Equation Models in the Social Sciences.San Francisco: Jossey-Bass.
4.
Goodman, L.A. (1976) "The relationship between modified and usual multiple-regression approaches to the analysis of dichotomous variables," pp. 83-110 in D. R. Heise (ed.) Sociological Methodology1976. San Francisco: Jossey-Bass.
5.
Holt, D. (1979) "Log-linear models for contingency table analysis: on the interpretation of parameters."Soc. Methods and Research7: 330-336
6.
. Nelder, J.A. and R.W.M. Wedderburn (1972) "Generalized linear models."J. of the Royal Statistical Society (Series A) 135: 370-384.
