Exploring and Analyzing Monitoring the Future Data: A Primer

a Workshop

Patricia Berglund (University of Michigan)
Deborah Kloska (University of Michigan)

Monday, 5/20/2019 to 5/22/2019.   ARCHIVED EVENT

Location: Ann Arbor, MI

The Monitoring the Future (MTF) project is a long-term epidemiologic and etiologic study of substance use among the nation's youth and adults. Cross-sectional annual data are collected from surveys of nationally representative samples of high school seniors (since 1975) and 8th and 10th graders (since 1991). In all, approximately 50,000 students annually respond to approximately 100 drug use and demographic questions, as well as approximately 200 questions on subjects such as attitudes toward government, social institutions, race relations, changing gender roles, educational aspirations, occupational aims, and marital plans. The longitudinal panel study component collects data using biennial follow-up mail surveys with subsamples of about 2,450 respondents from each senior year class since 1976, spanning ages 19 to 30.

This free workshop will introduce participants to the MTF cross-sectional data (public-use and restricted-use) and the restricted-use longitudinal panel data available from the ICPSR/NAHDAP archives. The workshop will cover the content of MTF public release and restricted-use data, study documentation, data management and analysis planning, and a variety of analytic techniques appropriate for data derived from a complex sample design. The workshop format will be a combination of lectures, discussion, and demonstrations followed by guided lab sessions for participants to work with a subset of MTF restricted-use data.

Prerequisites: Strong interest in analyzing MTF data for publication in peer-reviewed journals or similar reports; excellent understanding of descriptive and regression analysis techniques; and demonstrated ability to use statistical software coding or syntax (rather than a GUI interface) for data management and data analysis. Familiarity with MTF public-use data is helpful but not required.

Eligibility: The workshop is designed for researchers who have an interest in using the MTF restricted-use data.

Application: Admission to this workshop is competitive. Enrollment will be limited to 20 participants. Apply using the ICPSR Summer Program portal. Please upload the following documents with your application:

Current curriculum vitae
Cover letter summarizing your previous experience with the MTF data, your research interests as related to the use of the MTF restricted-use data, and how attending this workshop will help meet your research or educational goals

Application Deadline: Friday, April 5, 2019. Successful applicants will be notified by Monday, April 15, 2019 of their acceptance.

Course Times: Registration: 8:30 am Monday; Course: 9:00am - 4:00pm Monday and Tuesday, and 9:00am - 2:30pm Wednesday

For more information, contact sumprog@icpsr.umich.edu or (734) 763-7400.


Patricia A. Berglund is a Senior Research Associate in the Survey Methodology Program at the Institute for Social Research. She has extensive experience in the use of computing systems for data management and complex sample survey data analysis. She works on research projects in youth substance abuse, adult mental health, and survey methodology using data from Army STARRS, Monitoring the Future, the National Comorbidity Surveys, World Mental Health Surveys, and other data sources. In addition, she is involved in development, implementation, and teaching of analysis courses and computer training programs at the Survey Research Center-Institute for Social Research. She also lectures in the SAS® Institute-Business Knowledge Series.

Deborah Kloska is a Data Analyst with the Youth & Social Issues Program. She received her BS in 1986 in Statistics and Psychology and MA in Applied Statistics in 2001, both from the University of Michigan. Her analytical interests focus on applying up-to-date knowledge of statistical methods and procedures in the area of substance use, especially as related to longitudinal data analysis and complex survey design.

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