The Department of Biostatistics at the Johns Hopkins Bloomberg School of Public Health proposes an Environmental Biostatistics pre-doctoral training program to support four (4) trainees. The program entails two+ years of course work followed by examinations and a research thesis. Training grant support will be provided for the initial 3 years; research assistantships will fund the remaining training period. The program will be located in the Department of Biostatistics and be supported by faculty in the Departments of Biostatistics, Environmental Health Sciences, Epidemiology, Health Services Research, and Molecular Microbiology and Immunology. Through course work, seminars, participation in working groups and directed doctoral research, the investigators shall educate the next generation of leaders in development and application of biostatistical science to environmental research and policy. They shall integrate biostatistics and biostatisticians with other environmental sciences in an educational climate ideally suited to fostering lasting relationships among graduate students and faculty in biostatistics and other fields. As a result, the graduates will effectively collaborate across disciplines, identify the key methodologic needs, then develop and apply statistical approaches that address these needs. Graduates will effectively communicate substantive findings to scientists, policy makers and the general public. Program and affiliated faculty are committed to honoring this philosophy and to achieving these goals.

Agency
National Institute of Health (NIH)
Institute
National Institute of Environmental Health Sciences (NIEHS)
Type
Institutional National Research Service Award (T32)
Project #
1T32ES012871-01
Application #
6748880
Study Section
Environmental Health Sciences Review Committee (EHS)
Program Officer
Shreffler, Carol K
Project Start
2004-07-12
Project End
2009-06-30
Budget Start
2004-07-12
Budget End
2005-06-30
Support Year
1
Fiscal Year
2004
Total Cost
$91,486
Indirect Cost
Name
Johns Hopkins University
Department
Biostatistics & Other Math Sci
Type
Schools of Public Health
DUNS #
001910777
City
Baltimore
State
MD
Country
United States
Zip Code
21218
Krall, Jenna R; Hackstadt, Amber J; Peng, Roger D (2017) A hierarchical modeling approach to estimate regional acute health effects of particulate matter sources. Stat Med 36:1461-1475
Lum, Kirsten J; Sundaram, Rajeshwari; Barr, Dana B et al. (2017) Perfluoroalkyl Chemicals, Menstrual Cycle Length, and Fecundity: Findings from a Prospective Pregnancy Study. Epidemiology 28:90-98
Fisher, Aaron; Caffo, Brian; Schwartz, Brian et al. (2016) Fast, Exact Bootstrap Principal Component Analysis for p > 1 million. J Am Stat Assoc 111:846-860
Lum, Kirsten J; Sundaram, Rajeshwari; Louis, Thomas A (2015) Accounting for length-bias and selection effects in estimating the distribution of menstrual cycle length. Biostatistics 16:113-28
Peng, Roger D; Butz, Arlene M; Hackstadt, Amber J et al. (2015) Estimating the health benefit of reducing indoor air pollution in a randomized environmental intervention. J R Stat Soc Ser A Stat Soc 178:425-443
Goldsmith, Jeff; Huang, Lei; Crainiceanu, Ciprian M (2014) Smooth Scalar-on-Image Regression via Spatial Bayesian Variable Selection. J Comput Graph Stat 23:46-64
Gellar, Jonathan E; Colantuoni, Elizabeth; Needham, Dale M et al. (2014) Variable-Domain Functional Regression for Modeling ICU Data. J Am Stat Assoc 109:1425-1439
Hackstadt, Amber J; Matsui, Elizabeth C; Williams, D'Ann L et al. (2014) Inference for environmental intervention studies using principal stratification. Stat Med 33:4919-33
Hackstadt, Amber J; Peng, Roger D (2014) A Bayesian Multivariate Receptor Model for Estimating Source Contributions to Particulate Matter Pollution using National Databases. Environmetrics 25:513-527
Bobb, Jennifer F; Dominici, Francesca; Peng, Roger D (2013) Reduced hierarchical models with application to estimating health effects of simultaneous exposure to multiple pollutants. J R Stat Soc Ser C Appl Stat 62:

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