Subject-specific odds ratios in binomial GLMMs with continuous response

Statistical Methods and Applications (Impact Factor: 0.35). 02/2008; 17(3):309-320. DOI: 10.1007/s10260-007-0060-x
Source: RePEc

ABSTRACT In a regression context, the dichotomization of a continuous outcome variable is often motivated by the need to express results
in terms of the odds ratio, as a measure of association between the response and one or more risk factors. Starting from the
recent work of Moser and Coombs (Stat Med 23:1843–1860, 2004) in this article we explore in a mixed model framework the possibility
of obtaining odds ratio estimates from a regression linear model without the need of dichotomizing the response variable.
It is shown that the odds ratio estimators derived from a linear mixed model outperform those from a binomial generalized
linear mixed model, especially when the data exhibit high levels of heterogeneity.

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