The long-term goals of this grant are to develop study designs and methods of statistical analysis for epidemiologic research of cancer and other chronic diseases. In this proposal, we focus on case-control studies in three broad aims: The first is to develop case-control design and analysis solutions to a number of important problems we have identified based on our applied work on """"""""standard""""""""' and counter matched case-control studies. These include appropriate analysis of case-control studies with random digit dial controls, Mantel-Haenszel and polytomous logistic regression estimators for studies with complex control selection, development of new population based case-control study designs that use inexpensive correlate exposure information to improve cost-efficiency, and analysis of case-control studies with missing covariate data. The second is to develop efficiency bound methods appropriate to case-control study designs as well as investigate estimation methods that make use of cohort or external information to improve case-control study efficiency. These results will clarify when auxiliary at-risk and covariate information can be used to improve efficiency in analysis of nested case-control studies and provide methods that exploit this information.
The third aim i s outreach to investigators interested in the methods including maintaining software and data examples on our website and limited consultation. The impact of these projects is to expand the design and analysis """"""""tools""""""""' available to epidemiologic research in a way that will improve validity and cost-efficiency. ? ?

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project (R01)
Project #
5R01CA042949-18
Application #
6921428
Study Section
Biostatistical Methods and Research Design Study Section (BMRD)
Program Officer
Tiwari, Ram C
Project Start
1986-07-01
Project End
2007-08-31
Budget Start
2005-09-01
Budget End
2006-08-31
Support Year
18
Fiscal Year
2005
Total Cost
$243,875
Indirect Cost
Name
University of Southern California
Department
Public Health & Prev Medicine
Type
Schools of Medicine
DUNS #
072933393
City
Los Angeles
State
CA
Country
United States
Zip Code
90089
Rakovski, Cyril; Langholz, Bryan (2015) A post-hoc Unweighted Analysis of Counter-Matched Case-Control Data. Int J Biostat 11:223-32
Figueiredo, Jane C; Haile, Robert W; Bernstein, Leslie et al. (2010) Oral contraceptives and postmenopausal hormones and risk of contralateral breast cancer among BRCA1 and BRCA2 mutation carriers and noncarriers: the WECARE Study. Breast Cancer Res Treat 120:175-83
Gebregziabher, Mulugeta; Langholz, Bryan (2010) A semiparametric missing-data-induced intensity method for missing covariate data in individually matched case-control studies. Biometrics 66:845-54
Langholz, Bryan; Richardson, David (2009) Are nested case-control studies biased? Epidemiology 20:321-9
Langholz, Bryan; Thomas, Duncan C; Stovall, Marilyn et al. (2009) Statistical methods for analysis of radiation effects with tumor and dose location-specific information with application to the WECARE study of asynchronous contralateral breast cancer. Biometrics 65:599-608
Berhane, Kiros; Hauptmann, Michael; Langholz, Bryan (2008) Using tensor product splines in modeling exposure-time-response relationships: application to the Colorado Plateau Uranium Miners cohort. Stat Med 27:5484-96
Stovall, Marilyn; Smith, Susan A; Langholz, Bryan M et al. (2008) Dose to the contralateral breast from radiotherapy and risk of second primary breast cancer in the WECARE study. Int J Radiat Oncol Biol Phys 72:1021-30
Figueiredo, Jane C; Bernstein, Leslie; Capanu, Marinela et al. (2008) Oral contraceptives, postmenopausal hormones, and risk of asynchronous bilateral breast cancer: the WECARE Study Group. J Clin Oncol 26:1411-8
Bernstein, Jonine L; Langholz, Bryan; Haile, Robert W et al. (2004) Study design: evaluating gene-environment interactions in the etiology of breast cancer - the WECARE study. Breast Cancer Res 6:R199-214
Faucett, C L; Thomas, D C (1996) Simultaneously modelling censored survival data and repeatedly measured covariates: a Gibbs sampling approach. Stat Med 15:1663-85

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