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Modeling and variable selection in epidemiologic analysis.

S Greenland

Division of Epidemiology, University of California, School of Public Health, Los Angeles 90024.

This paper provides an overview of problems in multivariate modeling of epidemiologic data, and examines some proposed solutions. Special attention is given to the task of model selection, which involves selection of the model form, selection of the variables to enter the model, and selection of the form of these variables in the model. Several conclusions are drawn, among them: a) model and variable forms should be selected based on regression diagnostic procedures, in addition to goodness-of-fit tests; b) variable-selection algorithms in current packaged programs, such as conventional stepwise regression, can easily lead to invalid estimates and tests of effect; and c) variable selection is better approached by direct estimation of the degree of confounding produced by each variable than by significance-testing algorithms. As a general rule, before using a model to estimate effects, one should evaluate the assumptions implied by the model against both the data and prior information.

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				W. Koenig, H. Lowel, J. Baumert, and C. Meisinger C-Reactive Protein Modulates Risk Prediction Based on the Framingham Score: Implications for Future Risk Assessment: Results From a Large Cohort Study in Southern Germany Circulation, March 23, 2004; 109(11): 1349 - 1353. [Abstract] [Full Text] [PDF]

				R. Morley, M. S. Fewtrell, R. A. Abbott, T. Stephenson, U. MacFadyen, and A. Lucas Neurodevelopment in Children Born Small for Gestational Age: A Randomized Trial of Nutrient-Enriched Versus Standard Formula and Comparison With a Reference Breastfed Group Pediatrics, March 1, 2004; 113(3): 515 - 521. [Abstract] [Full Text] [PDF]

				C. S. Anderson, V. Feigin, D. Bennett, R.-B. Lin, G. Hankey, K. Jamrozik, and for the Australasian Cooperative Research on Subar Active and Passive Smoking and the Risk of Subarachnoid Hemorrhage: An International Population-Based Case-Control Study Stroke, March 1, 2004; 35(3): 633 - 637. [Abstract] [Full Text] [PDF]

				E. T. Chang, T. Zheng, E. G. Weir, M. Borowitz, R. B. Mann, D. Spiegelman, and N. E. Mueller Aspirin and the Risk of Hodgkin's Lymphoma in a Population-Based Case-Control Study J Natl Cancer Inst, February 18, 2004; 96(4): 305 - 315. [Abstract] [Full Text] [PDF]

				R. Hachamovitch, S. W. Hayes, J. D. Friedman, I. Cohen, and D. S. Berman Stress myocardial perfusion single-photon emission computed tomography is clinically effective and cost effective in risk stratification of patients with a high likelihood of coronary artery disease (CAD) but no known CAD J. Am. Coll. Cardiol., January 21, 2004; 43(2): 200 - 208. [Abstract] [Full Text] [PDF]