Integrated Data Analysis for Addiction Research
Lately there has been an increased call for secondary data analysis of existing datasets in order to maximize the existing public investment in the collection of research data. However, researchers often find that existing individual data sets are inadequate for testing secondary hypotheses in terms of small sample sizes, lack of heterogeneity on key characteristics, and differences in the ways constructs are measure. Integrated data analysis (IDA) allows for the pooling of separate data sets to create larger, more heterogeneous data sets that can be used to test hypotheses, despite differences across studies in populations, study design, and measurement. Unlike data harmonization which requires identical measures across datasets, IDA allows for the development of measures that are psychometrically equivalent across data sets. This training workshop will introduce researchers to the IDA method and to statistical methods for the development of measures that are equivalent across data sets using a pooled data set that combines:
- Multiple years of the National Survey on Drug Use and Health (NSDUH), and
- National Epidemiologic Survey on Alcohol and Related Conditions (NESARC: Wave 1)
Participants will learn the IDA process and, through hands-on training, how to develop a psychometrically equivalent measure of nicotine dependence across studies and levels of smoking exposure. SAS and Mplus statistical software packages will be used.
Prerequisites: Participants are expected to have a basic understanding of secondary data, fundamental data analysis skills, basic knowledge of SAS and Mplus, and a substantive interest in substance use and dependence. Basic knowledge of factor analysis/structural equation modeling would be helpful.
Application: Admission to this workshop is competitive. Enrollment is limited to 25 participants. Apply using the Summer Program portal (by clicking on the "Registration & Fees" tab at the top of this page) to provide your information, select the course, and complete the section on your quantitative/statistical experience. Also, upload the following documents via the portal:
- Current curriculum vita
- Cover letter summarizing research interests and experiences
Stipend: A limited number of needs-based stipends are available to help with travel and housing costs. To be considered for a stipend, applicants must clearly indicate aid needed in the cover letter and also submit a letter of support from a senior faculty member, mentor, or adviser.
Deadline: Deadline for application is June 1, 2013.
Fee: There are no tuition fees for accepted participants.