This application seeks support from the National Institute on Drug Abuse R25 mechanism for pre-doctoral and postdoctoral research positions at the Virginia Institute for Psychiatric and Behavioral Genetics (VIPBG) at Virginia Commonwealth University (VCU). The overall goal of this research education program is to provide an environment that encourages the development and application of statistical genetics at the highest levels. To accomplish this goal, a research education program in statistical genetics will been developed to foster interdisciplinary research, a key tenet of the NIDA mission, and which we believe is essential to conducting research in this field. Two areas of research focus are identified: Advanced Genetic Epidemiology and Statistical Molecular Genetics. These areas are synergistic and address a diverse variety of statistical methods, both those in current use and those under development. The research education program consists of pre-doctoral and postdoctoral components. Pre-doctoral participants will pursue degrees in either Human and Molecular Genetics or Biostatistics. This component is designed to recruit, at the earliest time in their careers, potential future investigators to research in statistical genetics focused on substance use, abuse and dependence (SUAD).
The aim i s to create a cohort of PhD graduates who are have been extensively exposed to, and begun to publish research in, this area at the outset of their research training. The postdoctoral component recognizes that many promising young researchers have training in areas relevant to, but not focused on, the statistical genetics of substance use and abuse. This flexible 2-3 year postdoctoral training component will help guide young investigators to this field of study and will provide them with integrated and focused training that will enable them to pursue careers in statistical genetics of SUAD. Research education is intended for individuals with training in mathematics, statistics, biostatistics, genetics, psychology or pharmacology and to those who have completed their clinical requirements for the MD degree. The goal of the postdoctoral component is to educate independent investigators who will contribute to the efforts to identify and characterize the genetic and environmental determinants of SUAD;they are expected to do so at VCU and at other institutions nationwide. To accomplish the overall program goal we will: i) Offer and carefully monitor a multidisciplinary integrated research training program with a range of research opportunities;ii) Meet the needs for training in emerging research areas in SUAD;iii) Provide training to researchers from diverse academic and ethnic backgrounds and intensive mentoring;iv) Provide a specialized curriculum that will merge strengths in SUAD research at our institution;and v) Disseminate course materials, developed software, user guides and example scripts to the wider community by teaching workshops and establishing a website with web casts, pod casts and script libraries.

Public Health Relevance

This project seeks support from the NIDA R25 research education program in statistical genetics of substance abuse. Two pre-doctoral and three postdoctoral participants will pursue individualized courses of training in statistical genetics, and participate in active research projects in the Virginia Institute for Psychiatric and Behavioral Genetics at Virginia Commonwealth University.

Agency
National Institute of Health (NIH)
Institute
National Institute on Drug Abuse (NIDA)
Type
Education Projects (R25)
Project #
5R25DA026119-04
Application #
8079020
Study Section
Special Emphasis Panel (ZDA1-MXH-H (16))
Program Officer
Weinberg, Naimah Z
Project Start
2008-09-30
Project End
2013-05-31
Budget Start
2011-06-01
Budget End
2012-05-31
Support Year
4
Fiscal Year
2011
Total Cost
$452,875
Indirect Cost
Name
Virginia Commonwealth University
Department
Psychiatry
Type
Schools of Medicine
DUNS #
105300446
City
Richmond
State
VA
Country
United States
Zip Code
23298
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Pritikin, Joshua N; Rappaport, Lance M; Neale, Michael C (2017) Likelihood-based confidence intervals for a parameter with an upper or lower bound. Struct Equ Modeling 24:395-401

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