This project focuses on developing new statistical methods, and applying new and existing statistical techniques, to analyze data from laboratory animal studies. Much of our research dealt with tumor incidence, which is the rate at which new tumors arise. We investigated methods that handle complex data structures without relying on unrealistic assumptions. An analysis was developed which permits simultaneous inference about tumors at multiple sites while accounting for within-animal correlations among tumor onset times.

Agency
National Institute of Health (NIH)
Institute
National Institute of Environmental Health Sciences (NIEHS)
Type
Intramural Research (Z01)
Project #
1Z01ES045007-06
Application #
6672924
Study Section
(BB)
Project Start
Project End
Budget Start
Budget End
Support Year
6
Fiscal Year
2002
Total Cost
Indirect Cost
Name
U.S. National Inst of Environ Hlth Scis
Department
Type
DUNS #
City
State
Country
United States
Zip Code
Dinse, Gregg E; Peddada, Shyamal D (2011) Comparing tumor rates in current and historical control groups in rodent cancer bioassays. Stat Biopharm Res 3:97-105
Wang, Qihua; Dinse, Gregg E (2011) Linear regression analysis of survival data with missing censoring indicators. Lifetime Data Anal 17:256-79
Dinse, Gregg E; Peddada, Shyamal D; Harris, Shawn F et al. (2010) Comparison of NTP historical control tumor incidence rates in female Harlan Sprague Dawley and Fischer 344/N Rats. Toxicol Pathol 38:765-75
Song, Xinyuan; Sun, Liuquan; Mu, Xiaoyun et al. (2010) Additive hazards regression with censoring indicators missing at random. Can J Stat 38:333-351
Dunson, David B; Dinse, Gregg E (2002) Bayesian models for multivariate current status data with informative censoring. Biometrics 58:79-88
Dinse, G E; Umbach, D M; Sasco, A J et al. (1999) Unexplained increases in cancer incidence in the United States from 1975 to 1994: possible sentinel health indicators? Annu Rev Public Health 20:173-209