# Uncertainty Analysis of Multiple Epidemiological Studies Using Frequency Distributions of Relative Risks

### Proceed. ISUMA- NAFIPS '95 Third International Symposium on Uncertainty Modeling and Analysis, and Annual Conference of the North American Fuzzy Information Processing Society. IEEE Computing Society Press, 1995, pp. 40-45.

## Abstract

A new format for presenting uncertainty in the results of multiple epidemiologic
studies of the same outcome is suggested. A set of 95% confidence intervals for
relative risk, *RR*, is transformed to a frequency distribution of the normalized
deviations, *ln(RR)/SE(ln(RR))*, from the null value *ln(RR)=0 (RR=1)*.
I assume that deviations from *RR=1* are due to unaccounted residual biases and
compare the distribution of these deviations with the distribution of the actual
errors in physical measurements where the true values have subsequently become
known, and the incidence of large errors can be estimated. Comparison of these
distributions can, by analogy, help to understand how convincing is the evidence
of elevated risk in observational studies.

#### Keywords: uncertainty analysis, relative risks, epidemiological studies, observational studies

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