Log-Linear Techniques and the Regression Analysis of Dummy Dependent Variables

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Abstract
Although previous comparisons of log-linear techniques with the regression analysis of dummy dependent variables have focused on the statistical superiority of the log-linear techniques, this paper presents three advantages of dummy dependent-variable regressions. First, dummy dependent-variable regression is able to accommodate both categorical and continuous independent variables. Second, the calculation of indirect effects and reciprocal effects is possible only with dummy dependent-variable regression. Third, the slopes yielded by dummy dependent-variable regression possess the properties of fundamental parameters; the effect parameters of log-linear models do not. In particular, controlling for a variable that is irrelevant to the causal system under investigation can yield a partial relationship whose expected value differs from that of the zero-order relationship when using log-linear techniques.