ICPSR Summer Program in Quantitative Methods of Social Research

The ICPSR Summer Program provides in-depth, hands-on training in statistical techniques and research methodologies used across the social, behavioral, and medical sciences. We strive to fulfill the needs of researchers throughout their careers by offering instruction on a broad range of topics, ranging from introductory statistics to advanced quantitative methods and cutting-edge techniques. Our participants include graduate students, post-docs, faculty, researchers, and policy analysts from more than 350 universities, institutions, and organizations around the world.
From May through August 2017, the Summer Program will offer more than 80 courses in cities across the US and around the world. Registration is now open for all 2017 courses. For more information, visit icpsr.umich.edu/sumprog or contact sumprog@icpsr.umich.edu or (734) 763-7400.
The Summer Program’s Four-week Sessions provide comprehensive training in statistics and quantitative methods in a supportive social environment that facilitates professional networking, encourages the exchange of ideas, and makes the experience of acquiring critical analytical skills enjoyable. Our First (June 26 – July 21, 2017) and Second (July 24 – August 18, 2017) Sessions contain more than 35 courses, including regression analysis, Bayesian analysis, network analysis, longitudinal analysis, game theory, MLE, SEM, causal inference, and more. The four-week sessions take place on the University of Michigan campus in Ann Arbor. Scholarships are available for graduate students in sociology and public policy; applications are due March 31, 2017.
For researchers needing to learn a specific methodological technique in just a few days, the ICPSR Summer Program offers more than 40 short workshops, including:
  • Network Analysis: An Introduction (May 8-12, Ann Arbor)
  • Network Analysis: Statistical Approaches (May 15-19, Ann Arbor)
  • Regression Models for Categorical Outcomes: Specification, Estimation, and Interpretation (May 23-26, Amherst)
  • Latent Growth Curve Models (LGCM): A Structural Equation Modeling Approach (June 5-9, Chapel Hill)
  • Item Response Theory: Methods for the Analysis of Discrete Survey Response Data (June 5-9, Ann Arbor)
  • Applied Multilevel Models for Longitudinal and Clustered Data (June 5-9, Boulder)
  • Group-based Trajectory Modeling for the Medical and Social Sciences (June 12-14, Amherst)
  • Growth Mixture Models: A Structural Equation Modeling Approach (June 12-14, Chapel Hill)
  • FREE WORKSHOP: Panel Study of Income Dynamics (PSID) Data User Workshop (June 12-16, Ann Arbor)
  • Doing Bayesian Data Analysis: An Introduction (June 20-23, Ann Arbor)
  • Structural Equation Models and Latent Variables: An Introduction (July 10-14, Ann Arbor)
  • FREE WORKSHOP: Health Disparities, Health Inequities and Vulnerable Populations: Research Examining and Understanding Complexity (July 10-14, Ann Arbor)
  • Introduction to Mixed Methods Research (July 12-14, Chapel Hill)
  • Managing Data for Reproducible Results (July 24-28, Ann Arbor)
  • Statistical Graphics (July 31 – Aug. 2, Chapel Hill)
  • Social Network Analysis (July 31 – Aug. 4, Boulder)
  • Qualitative Research Methods (Aug. 2-4, Chapel Hill)
  • Latent Class Analysis in Social Science Research (Aug. 7-11, Berkeley)

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