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The advantage of using multilevel modeling is that it takes the hierarchical structure of the data into account by specifying random effects at each level of analysis, and thus results in a more conservative inference for the aggregate effect. The study discussed in this paper combines data from two databases for analysis. Data from the National Occupational Mortality Surveillance System (NOMS) containing individual-level information from death certificates was linked by occupation to the Occupational Information Network (ONET) which contains job characteristics at the occupational level. This paper examines the adjusted association between job characteristics and select causes of death. A recently available generalized linear mixed models procedure, PROC GLIMMIX, was used to fit the multilevel logistic regression model to the data.

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Format:PDFSize:132 KB
Date:Feb 2006
Pages:5

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