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Research Methods in Occupational Epidemiology$
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Harvey Checkoway, Neil E. Pearce, and David Kriebel

Print publication date: 2004

Print ISBN-13: 9780195092424

Published to Oxford Scholarship Online: September 2009

DOI: 10.1093/acprof:oso/9780195092424.001.0001

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Advanced Statistical Analysis

Advanced Statistical Analysis

Chapter:
(p.263) 9 Advanced Statistical Analysis
Source:
Research Methods in Occupational Epidemiology
Author(s):

Harvey Checkoway

Neil Pearce

David Kriebel

Publisher:
Oxford University Press
DOI:10.1093/acprof:oso/9780195092424.003.0009

Stratified analyses may not be feasible if there are multiple exposure categories or two or more than two or three confounders. In this situation, multiple regression methods are required. This chapter presents an overview of the methods that are used for analyzing occupational epidemiology data. It begins with a presentation of the basic multiple linear regression model used when the outcome of interest in measured as a continuous variable. This is followed by a presentation of generalized estimating equation (GEE) methods in the context of repeated measures analysis. The general form of the log-linear model is then introduced. The specific forms of Poisson regression (for cohort studies), the Cox proportional hazards model (for survival studies), and logistic regression (for case-control studies) are then defined and illustrated with occupational epidemiology examples. Various aspects of model specification are considered, including variable specification, estimation of joint effects, exposure-response estimation, and regression diagnostics.

Keywords:   Cox proportional hazards model, data analysis, generalize estimating equations, GEE, log-linear models, logistic regression, Poisson regression, regression modeling

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