Abstract

The specific aims of the Biostatistical and Informatics Core are:
Aim 1 : To provide the statistical, mathematical, and data management support required to accomplish the specific aim of the individual projects and cores.
Aim2. To assist in the design and analysis of new projects and studies arising from the results of the proposed studies.
Aim 3 : To assist individual investigators and other Core facilities in the collection and management of required data.
Aim 4 : To facilitate the exchange of data and information between the separate data systems of the individual Projects and Cores.
Aim 5 : To establish and maintain a central data management system in which data pertaining to each study subject will be maintained and coordinated.
Aim 6 : To oversee quality control, security, confidentiality, and audit procedures.

  Funding Agency

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Program Projects (P01)
Project #
5P01CA082710-03
Application #
6505557
Study Section
Subcommittee E - Prevention &Control (NCI)
Project Start
2001-09-27
Project End
2002-08-31
Budget Start
Budget End
Support Year
3
Fiscal Year
2001
Total Cost
Indirect Cost

  Institution

Name
University of Texas MD Anderson Cancer Center
Department
Type
DUNS #
001910777
City
Houston
State
TX
Country
United States
Zip Code
77030

  Publications

Montealegre, J R; Peckham-Gregory, E C; Marquez-Do, D et al. (2018) Racial/ethnic differences in HPV 16/18 genotypes and integration status among women with a history of cytological abnormalities. Gynecol Oncol 148:357-362
Montealegre, Jane R; Varier, Indu; Bracamontes, Christina G et al. (2017) Racial/ethnic variation in the prevalence of vaccine-related human papillomavirus genotypes. Ethn Health :1-12
Zhu, Hongxiao; Morris, Jeffrey S; Wei, Fengrong et al. (2017) Multivariate functional response regression, with application to fluorescence spectroscopy in a cervical pre-cancer study. Comput Stat Data Anal 111:88-101
Yang, Jingjing; Cox, Dennis D; Lee, Jong Soo et al. (2017) Efficient Bayesian hierarchical functional data analysis with basis function approximations using Gaussian-Wishart processes. Biometrics 73:1082-1091
Nghiem, Van T; Davies, Kalatu R; Beck, J Robert et al. (2016) Overtreatment and Cost-Effectiveness of the See-and-Treat Strategy for Managing Cervical Precancer. Cancer Epidemiol Biomarkers Prev 25:807-14
Nghiem, Van T; Davies, Kalatu R; Chan, Wenyaw et al. (2016) Disparities in cervical cancer survival among Asian-American women. Ann Epidemiol 26:28-35
Bodenschatz, Nico; Lam, Sylvia; Carraro, Anita et al. (2016) Diffuse optical microscopy for quantification of depth-dependent epithelial backscattering in the cervix. J Biomed Opt 21:66001
Sheikhzadeh, Fahime; Ward, Rabab K; Carraro, Anita et al. (2015) Quantification of confocal fluorescence microscopy for the detection of cervical intraepithelial neoplasia. Biomed Eng Online 14:96
Yamal, Jose-Miguel; Guillaud, Martial; Atkinson, E Neely et al. (2015) Prediction using hierarchical data: Applications for automated detection of cervical cancer. Stat Anal Data Min 8:65-74
Montealegre, Jane R; Landgren, Rachel M; Anderson, Matthew L et al. (2015) Acceptability of self-sample human papillomavirus testing among medically underserved women visiting the emergency department. Gynecol Oncol 138:317-22

Showing the most recent 10 out of 110 publications