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 (Odds ratios for a continuous outcome variable without dichotomizing, Statistics in Medicine, 2004, 23, 1843-1860), 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.

SCIANDRA, M., MUGGEO, V., & LOVISON, G. (2008). Subject-specific odds ratios in binomial GLMMs with continuous response. STATISTICAL METHODS & APPLICATIONS, 17(3), 309-320 [10.1007/s10260-007-0060-x].

Subject-specific odds ratios in binomial GLMMs with continuous response

SCIANDRA, Mariangela;MUGGEO, Vito Michele Rosario;LOVISON, Gianfranco
2008

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 (Odds ratios for a continuous outcome variable without dichotomizing, Statistics in Medicine, 2004, 23, 1843-1860), 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.
Settore SECS-S/01 - Statistica
SCIANDRA, M., MUGGEO, V., & LOVISON, G. (2008). Subject-specific odds ratios in binomial GLMMs with continuous response. STATISTICAL METHODS & APPLICATIONS, 17(3), 309-320 [10.1007/s10260-007-0060-x].
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/10447/34970
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