EXPERIMENTAL DESIGN AND DATA ANALYSIS METHODOLOGY FOR ANIMAL EXPERIMENTS

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This project is concerned with statistical methodology issues in the design, analysis, and interpretation of laboratory animal experiments. Specific research efforts include (1) To address the false positive issue in long term rodent carcinogenicity studies, the use of statistical methodology that adjusts for multiple comparisons was investigated. An actual case study utilizing three different statistical decision rules to evaluate 25 NCI carcinogenicity studies was examined. Agreement among these decision rules was shown to be greater than originally reported. (2) Evaluation of results from the National Toxicology Program's carcinogenicity studies has resulted in the formulation and publication of an historical control tumor database and the identification of potential sources of variability in tumor rates. (3) Various experimental designs for assessing male reproductive function in rabbits were studied to determine whether they had sufficient power to detect a reasonably sized toxic effect. It was determined that studies which employed a preexposure period would be appropriate. (4) Statistical methods have been developed for extracting information on disease incidence from data on disease mortality. Under certain simplifying assumptions, the disease mortality rates can be expressed in terms of the incidence and lethality rates. The proposed approach is appropriate for the case in which there are two populations, one having data on disease incidence and disease lethality and the other having data on disease mortality. Based on a model linking the incidence rates in the two groups, the incidence rates in the second population can be estimated by maximizing a likelihood that involves only mortality data. Future research includes a comparison of statistical methodologies for evaluating tumor data that do not require cause of death determinations and assessing the effects of diet and caging protocols on variability in control tumor incidence.