In this paper we present an extension of the regression models to more than one response and more than one group of covariates, in a way that purely explanatory and intermediate variables can be modelled simultaneously. While we limit our examplification to continuous gaussian data, the method discussed is quite general and allows continuous, categorical and a mixture of quantitative and qualitative variables. This topic appears of utmost importance in Psychiatric Epidemiology and in particular in the evaluation of the outcomes of psychiatric care. In fact, in psychiatry the effects of treatments should be evaluated using multiple measures exploring many areas, for example including psychopathology, social disability, quality of life, service satisfaction and service utilisation.
Regression analysis of multiple outcomes
STANGHELLINI, Elena;
2001
Abstract
In this paper we present an extension of the regression models to more than one response and more than one group of covariates, in a way that purely explanatory and intermediate variables can be modelled simultaneously. While we limit our examplification to continuous gaussian data, the method discussed is quite general and allows continuous, categorical and a mixture of quantitative and qualitative variables. This topic appears of utmost importance in Psychiatric Epidemiology and in particular in the evaluation of the outcomes of psychiatric care. In fact, in psychiatry the effects of treatments should be evaluated using multiple measures exploring many areas, for example including psychopathology, social disability, quality of life, service satisfaction and service utilisation.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.