Path analysis and multi-criteria decision making: An approach for multivariate model selection and analysis in health

PURPOSE: This paper introduces an approach that includes non-quantitative f actors for the selection and assessment of multivariate complex models in h ealth. METHODS: A goodness-of-fit based methodology combined with fuzzy multi-crit eria decision-making approach is proposed for model selection. Models were obtained using the Path Analysis (PA) methodology in order to explain the i nterrelationship between health determinants and the post-neonatal componen t of infant mortality in 59 municipalities of Brazil in the year 1991. Soci oeconomic and demographic factors were used as exogenous variables, and env ironmental, health service and agglomeration as endogenous variables. Five PA models were developed and accepted by statistical criteria of goodness-o f fit. These models were then submitted to a group of experts, seeking to c haracterize their preferences, according to predefined criteria that tried to evaluate model relevance and plausibility, Fuzzy set techniques were use d to rank the alternative models according to the number of times a model w as superior to ("dominated") the others. RESULTS: The best,ranked model explained above 90% of the endogenous variab les variation, and showed the favorable influences of income and education levels on post-neonatal mortality. It also showed the unfavorable effect on mortality of fast population growth, through precarious dwelling condition s and decreased access to sanitation. CONCLUSIONS. It was possible to aggregate expert opinions in model evaluati on. The proposed procedure for model selection allowed the inclusion of sub jective information in a clear and systematic manner, (C) 2001 Elsevier Sci ence Inc. All rights reserved.