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American Journal of Epidemiology Vol. 147, No. 7: 615-619
Copyright © 1998 by The Johns Hopkins University School of Hygiene and Public Health
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Quantitative Evaluation of Multiplicity in Epidemiology and Public Health Research
University of Texas Medical Branch Galveston, Galveston, TX
Reprint requests to Dr. Kenneth J. Ottenbacher, SAHS, Rm. 4.202, University of Texas Medical Branch, 301 University Blvd., Galveston, TX 77755-1028.
Epidemiologic and public health researchers frequently include several dependent variables, repeated assessments, or subgroup analyses in their investigations. These factors result in multiple tests of statistical significance and may produce type 1 experimental errors. This study examined the type 1 error rate in a sample of public health and epidemiologic research. A total of 173 articles chosen at random from 1996 issues of the American Journal of Public Health and the American Journal of Epidemiology were examined to determine the incidence of type 1 errors. Three different methods of computing type 1 error rates were used: experiment-wise error rate, error rate per experiment, and percent error rate. The results indicate a type 1 error rate substantially higher than the traditionally assumed level of 5% (p < 0.05). No practical or statistically significant difference was found between type 1 error rates across the two journals. Methods to determine and correct type 1 errors should be reported in epidemiologic and public health research investigations that include multiple statistical tests. Am J Epidemiol 1998; 147: 615–19.
bias (epidemiology); probability; research design; significance tests
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