The goal of the research project is to carry out an extensive investigation of several areas of statistical methodology for the design and analysis of biomedical studies, planned or observational, applicable to various areas of health research including cancer, toxicology, environmental health and epidemiology. The objective is to provide more efficient statistical methods to achieve valid conclusions at less cost in terms of time and sample size. The research falls into four main categories: (a) Interim monitoring of clinica trials; (b) Design and analysis of long-term animal tumorigenicity bioassays; (c) Quality control procedures for laboratory tests; (d) General statistical methods for survival data. Specific projects include the use of repeated confidence intervals to monitor quantities of interest such as hazard ratios, odds ratio or median response time in follow-up studies. An important advantage of this approach is that its flexibility allows inferences to be drawn independent from any stopping rule. It is planned to investigate the design of efficient and robust interim sacrificing schedules in long-term animal studies. Statistical methods for describing association among incidence of distinct diseases from pathology data gathered from these experiments will also be studied. The existence of negative correlations, not demonstrable as spurious, could have serious implications concerning the definition of a """"""""carcinogen."""""""" Under the last category (d) several projects are planned, including development of methodology to analyze discrete time survival data with covariates and multiple end-points which can arise, for example, in a skin cancer study.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
2R01GM028364-07
Application #
3275679
Study Section
(SSS)
Project Start
1981-02-01
Project End
1991-01-31
Budget Start
1987-02-01
Budget End
1988-01-31
Support Year
7
Fiscal Year
1987
Total Cost
Indirect Cost
Name
Cornell University
Department
Type
DUNS #
City
Ithaca
State
NY
Country
United States
Zip Code
14850
Waller, L A; Turnbull, B W; Gustafsson, G et al. (1995) Detection and assessment of clusters of disease: an application to nuclear power plant facilities and childhood leukaemia in Sweden. Stat Med 14:3-16
Natarajan, R; Turnbull, B W; Slate, E H et al. (1994) A computer program for the statistical analysis of repeated event data using a mixed effects regression model. Comput Methods Programs Biomed 42:283-94
Jennison, C; Turnbull, B W (1993) Sequential equivalence testing and repeated confidence intervals, with applications to normal and binary responses. Biometrics 49:31-43
Jennison, C; Turnbull, B W (1993) Group sequential tests for bivariate response: interim analyses of clinical trials with both efficacy and safety endpoints. Biometrics 49:741-52
Waller, L A; Turnbull, B W (1993) The effects of scale on tests for disease clustering. Stat Med 12:1869-84
McShane, L M; Turnbull, B W (1992) Optimal checking procedures for monitoring laboratory analyses. Stat Med 11:1343-57
McShane, L M; Clark, L C; Combs Jr, G F et al. (1991) Reporting the accuracy of biochemical measurements for epidemiologic and nutrition studies. Am J Clin Nutr 53:1354-60
Turnbull, B W; Iwano, E J; Burnett, W S et al. (1990) Monitoring for clusters of disease: application to leukemia incidence in upstate New York. Am J Epidemiol 132:S136-43