The primary goal of the Data Core is to support and strengthen transdisciplinary research at Duke University and the University of North Carolina on the prevention of adolescent drug use. The Data Core provides resources and expertise that contribute to developing, executing, analyzing, and publishing prevention research. This research is focused on peer influence at three levels of analysis: intrapersonal, interpersonal, and institutional. At each level of analysis, specific sampling, design, data management, and statistical analysis concerns are salient. Members of the Data Core consult and, when appropriate, collaborate with Center investigators to ensure that these concerns are addressed in a rigorous and innovative manner.
The activities of Data Core members are motivated by four specific aims:
· provide leadership on the application of rigorous
and innovative statistical methods in Center research.
· provide data warehousing support that includes the establishment
of standards and consultation with Center investigators regarding data management;
storage and retrieval of electronic data; and quality control and assurance
of electronic data.
· promote collaborations between basic and applied researchers in the
Center and Data Core members.
· provide training opportunities in data acquisition, data management,
and data analysis for Center investigators.
These aims are fulfilled through personnel organized in a tripartite structure and directed by Dr. Rick Hoyle.
Data acquisition services, coordinated by Dr. Clara Muschkin, include:
· facilitating interaction with key personnel
in local schools
· reviewing protocols submitted to Institutional Review Boards
· reviewing Human Subjects sections of grant applications
· developing sampling designs and strategies
· locating and/or designing measures
· locating and acquiring archived data sets
Data management services, coordinated by Dr. Elizabeth Glennie, include:
· establishing procedures for data entry and
validity checking
· developing data safety and monitoring plans
· developing strategies to ensure respondent privacy
· securely archiving extant data
· designing codebooks and other documentation
· developing procedures for matching data sets from varied sources
· programming in SAS and selected data base software
Data analysis services, coordinated by Dr. Patrick Malone, include:
· consulting on research design, including factorial,
longitudinal, and multilevel designs
· determining sample size needs and evaluating statistical power
· reviewing and possibly collaborating on grant proposals and manuscripts
· consulting on statistical analyses
· programming in SAS, MPlus, HLM, and EQS
For access to information relevant to one of these areas, follow one of these links: