The principal aims of this project are to study a number of statistical problems associated with the analysis of epidemiologic data. Since odds ratios form the nucleus of many epidemiologic analyses, this research addresses issues in modeling building with odds ratios and more generally with relative risk or log-linear modeling. The research contrasts selected statistical estimation procedures. Computer and theoretical techniques are used to develop and compare the methodology. In addition, the methodology is applied to selected cancer case-control data sets, and these data sets are utilized in the comparisons and evaluations of the methods developed. In addition to methods associated with odds ratios, this grant proposes topics in analysis of survivorship data. Epidemiologic data often involve an outcome variable which represents the time to a specified event such as development of cancer. In this study, certain problems associated with the analysis of survivorship data are addressed and will be carefully studied through analytical and applied techniques. Where possible, data from existing case- control and the SEER registry at the University of Iowa will be utilized in the applications and comparisons. This research is a continuation of the previous two years of research in which a number of statistical problems have been studied. These problems are associated with methods for handling sparse multidimensional data. Such data are typical in epidemiological research and improved methods of analysis are needed. This research will lead to improved statistical methodology for the analysis of complex epidemiologic data. The issues studied have immediate implications for the analysis of such data.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project (R01)
Project #
5R01CA039065-06
Application #
3177803
Study Section
Epidemiology and Disease Control Subcommittee 2 (EDC)
Project Start
1985-09-01
Project End
1992-08-31
Budget Start
1990-09-01
Budget End
1992-08-31
Support Year
6
Fiscal Year
1990
Total Cost
Indirect Cost
Name
University of Iowa
Department
Type
Schools of Medicine
DUNS #
041294109
City
Iowa City
State
IA
Country
United States
Zip Code
52242
O'Gorman, T W; Woolson, R F; Jones, M P (1994) A comparison of two methods of estimating a common risk difference in a stratified analysis of a multicenter clinical trial. Control Clin Trials 15:135-53
O'Gorman, T W; Woolson, R F (1993) On the efficacy of the rank transformation in stepwise logistic and discriminant analysis. Stat Med 12:143-51
Woolson, R F; O'Gorman, T W (1992) A comparison of several tests for censored paired data. Stat Med 11:193-208
Davis, C S (1991) Statistical analysis of stratified 2x2 tables. Infect Control Hosp Epidemiol 12:173-8
Davis, C S (1991) A one degree of freedom nominal association model for testing independence in two-way contingency tables. Stat Med 10:1555-63
Joslyn, S; Lynch, C; Wallace, R et al. (1990) Relationship between diabetes mellitus mortality rates and drinking water magnesium levels in Iowa. Magnes Trace Elem 9:94-100
O'Gorman, T W; Woolson, R F; Jones, M P et al. (1990) Statistical analysis of K 2 x 2 tables: a comparative study of estimators/test statistics for association and homogeneity. Environ Health Perspect 87:103-7
Lynch, C F; Woolson, R F; O'Gorman, T et al. (1989) Chlorinated drinking water and bladder cancer: effect of misclassification on risk estimates. Arch Environ Health 44:252-9
Jones, M P; Crowley, J (1989) A general class of nonparametric tests for survival analysis. Biometrics 45:157-70
Jones, M P; O'Gorman, T W; Lemke, J H et al. (1989) A Monte Carlo investigation of homogeneity tests of the odds ratio under various sample size configurations. Biometrics 45:171-81

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