The Inter‑university Consortium for Political and Social Research (ICPSR) is pleased to announce the 2012 Summer Program in Quantitative Methods of Social Research. 



 



As many subscribers to this list already know, the main component of the ICPSR Summer Program is held on the campus of the University of Michigan, in Ann Arbor. Lectures and workshops on a wide variety of topics in research design, quantitative reasoning, statistical methods, and data processing are presented in two four‑week sessions. The first session runs from June 18, 2012 until July 13, 2012. The second session runs from July 16, 2012 until August 10, 2012. The contents of the two sessions are largely independent of each other. But, we do have an increasing number of course sequences that span the two sessions (i.e., an introductory workshop during the first session and advanced coverage of the same topic during the second session). So, there are some second‑session workshops that assume participants are familiar with material from first‑session courses (this should be clear from the course descriptions). 



 



The 2012 ICPSR Summer Program will also offer a number of three‑ to five‑day workshops on both statistical and substantive topics throughout the summer. Most of these shorter workshops take place in Ann Arbor, but there are several that will be held in other locations: Amherst, MA; Bloomington, IN; Chapel Hill, NC; Berkeley, CA., and (for the first time) Boulder, CO. 



 



The 2012 ICPSR Summer Program will include a total of 78 courses; 41 in the four-week sessions and 37 short workshops. We would like to draw your attention to several noteworthy features in the 2012 Program:



 



·         A 15% discount on registration fees for returning Summer Program participants.



 



·         Two new four-week workshops during the second session: “Network Analysis: Advanced Topics” and “Time Series Analysis: Advanced Topics.” 



 



·         A number of new three- to five-day statistical workshops (or classes returning after a hiatus), including: “Applied Power Analysis for the Social and Behavioral Sciences”, “Network Analysis: A Second Course”, “Network Analysis: Theory and Methods”, “Longitudinal Data Analysis, Including Categorical Outcomes”, “Time Series Analysis: A Second Course”, “Hierarchical Linear Models for Longitudinal Data”, “The R Statistical Computing Environment: The Basics and Beyond” (offered in Berkeley, CA), and “Growth Mixture Models: A Structural Equation Modeling Approach”.



 



·         A new emphasis on sequences of two courses—one introductory and one advanced—on the same topic. These occur in both the four-week sessions (e.g., “Introduction to Game Theory” during the first session and “Advanced Game Theory” during the second session) and among the short courses (e.g., “Time Series Analysis” An Introduction for Social Scientists” and “Time Series Analysis: A Second Course”). The two-course sequences are intended to help participants obtain solid understanding of a given subject matter during a relatively short period of time. In order to encourage participation in the course sequences, we are offering a 15% discount on registration fees for participants who take two (or more) related three- to five-day workshops (note that this discount is not applicable to the four-week sessions).



 



·         Continued emphasis on network analysis. In addition to the sequence of two courses in the four-week sessions (“Network Analysis” during the first session and “Network Analysis: Advanced Topics” during the second session), we will have the following short workshops: “Network Analysis: An Introduction”, “Social Network Analysis: An Introduction”, “Network Analysis: A Second Course”, “Analysis of Large-Scale Networks”, and “Network Analysis: Theory and Methods”.  



 



·         Two five-day workshops on the analysis of panel data: “Longitudinal Data Analysis, Including Categorical Outcomes” and on “Panel Data Analysis Using Stata.” 



 



·         Continued emphasis on multilevel modeling. In addition to the four-week workshop on “Applied Multilevel Models”, we offer the following short workshops: “Hierarchical Linear Models I: Introduction”, “Hierarchical Linear Models II: Special Topics”, “Applied Multilevel Models Using SAS and SPSS”, “Analyzing Multilevel and Mixed Models Using Stata”, and “Hierarchical Linear Models for Longitudinal Data.



 



In developing the course list for the 2012 ICPSR Summer Program, we are responding to the expressed interests of the social scientific research community, and providing coverage of statistical procedures that are receiving increasing attention within methodological circles. We hope you find something that will be useful for your own work in the 2012 Program. And, we are always interested in feedback: Please let us know if you have any thoughts about our current course offerings or new topics that you would like to see us include in the curriculum. 



 



The current course list for the 2012 ICPSR Summer Program is provided below. This list gives the complete set of statistical courses that the Program will offer in 2012. Note that the roster of short substantive workshops is still being put together; additional information will be provided on the Summer Program web site as it becomes available. 



 









Registration is now open for all of our statistical courses and for several of the substantive workshops. The application form, registration instructions, fee structure, and further information about the ICPSR Summer Program are all available on our web site:



 



     http://icpsr.umich.edu/sumprog/



 



Please feel free to e‑mail us with any further questions at: [log in to unmask]  



 



 



 



                                         2012 ICPSR SUMMER PROGRAM COURSE LIST



 



All classes are held in Ann Arbor, MI, unless otherwise noted.



 



First Four‑Week Session (June 18‑July 13, 2012):



 



Lectures:



 



Mathematics for Social Scientists, I 



Mathematics for Social Scientists, II



Mathematics for Social Scientists, III



Introduction to Computing



Introduction to the R Statistical Computing Environment



Introduction to the LaTeX Text Processing System



 



Statistical Workshops:



 



Introduction to Applied Bayesian Modeling for the Social Sciences



Introduction to Game Theory



Maximum Likelihood for Generalized Linear Models



Network Analysis



Rational Choice Theories of Politics and Society



Regression Analysis I: Introduction



Regression Analysis II: Linear Models



Regression Analysis III: Advanced Methods



Advanced Multivariate Statistical Methods



Introduction to Statistics and Data Analysis, I



Time Series Analysis



 



            Substantive Workshops:



 



Methodological Issues in Quantitative Research on Race and Ethnicity



Quantitative Analysis of Crime and Criminal Justice



 



            Blalock Lecture Series (Preliminary list of topics):



 



                  Data Mining



                  Latent Class Analysis



 



      Second Four‑Week Session (July 16‑August 10, 2012):



 



Lectures:



 



Introduction to Computing



Introductory/Review Lectures on Matrix Algebra



Introduction to the R Statistical Computing Environment



Introduction to the LaTeX Text Processing System



 



Statistical Workshops:



 



Advanced Bayesian Models for the Social Sciences



Categorical Data Analysis



Causal Inference for the Social Sciences



Complex Systems Models in the Social Sciences



Advanced Game Theory



Longitudinal Analysis



Longitudinal Analysis of Historical Demographic Data



Advanced Topics in Maximum Likelihood Estimation



Applied Multilevel Models



Advanced Multivariate Statistical Methods



Regression Analysis II: Linear Models



Simultaneous Equation Models



Introduction to Statistics and Data Analysis, II



Structural Equation Models with Latent Variables



 



            Blalock Lecture Series (Preliminary list of topics):                       



 



                  Missing Data: Statistical Analysis of Data with Incomplete Observations



                  Statistical Graphics for Visualizing Data



 



Two‑ to Five‑Day Statistical Workshops:



 



Network Analysis: An Introduction (May 29-June 1)



Network Analysis: A Second Course (June 4-8)



Spatial Econometrics: Statistical Models of Interdependence Among Observations (June 4-8)



Analyzing Developmental Trajectories (June 4-6, Amherst, MA)



Hierarchical Linear Models I (June 11-15, Amherst, MA)



Monte Carlo Simulation and Resampling Methods (June 11-15, Chapel Hill, NC)



Structural Equation Models and Latent Variables: An Introduction (June 11-15)



Doing Bayesian Data Analysis: An Introduction (June 11-15)



Analysis of Large-Scale Networks (June 18-22)



Introduction to Spatial Regression Analysis (June 18-22, Chapel Hill, NC)



Mixed Methods: Approaches for Combining Qualitative and Quantitative Research Strategies (June 25-27, Chapel Hill, NC)



Longitudinal Data Analysis, Including Categorical Outcomes (June 25-29)



Models for Categorical Outcomes Using Stata: Specification, Estimation, and Interpretation (June 25-29)



Causal Inference in the Social Sciences: Matching, Propensity Scores, and Other Strategies (July 9-13, Berkeley, CA)



Time Series Analysis: An Introduction for Social Scientists (July 9-13)



Panel Data Analysis Using Stata (July 9-13)



Applied Multilevel Models Using SAS and SPSS (July 9-13, Boulder, CO)



Item Response Theory (July 9-13, Boulder, CO)



Social Network Analysis: An Introduction (July 16-20, Chapel Hill, NC)



Time Series Analysis: A Second Course (July 16-20)



Applied Power Analysis for the Social and Behavioral Sciences (July 23-25)



Missing Data: An Introduction to the Analysis of Incomplete Data Sets (July 23-26, Bloomington, IN)



Designing, Conducting, and Analyzing Field Experiments (July 30-August 3)



Hierarchical Models for Longitudinal Data (August 6-8, Boulder, CO)



Latent Growth Curve Models (LGCM): A Structural Equation Modeling Approach (August 6-10, Chapel Hill, NC)



The R Statistical Computing Environment: The Basics and Beyond (August 6-9, Berkeley, CA)



Growth Mixture Models: A Structural Equation Modeling Approach (August 13-15, Chapel Hill, NC)



Analyzing Multilevel and Mixed Models Using Stata (August 13-15)



Hierarchical Linear Models II: Special Topics (TBD)



Network Analysis: Theory and Methods (Bloomington, IN, TBD)



 



        Three- to Five-Day Substantive Workshops:



 



Health Disparities Research and Minority Populations: Exploring ICPSR Data Sources (June 18-22)



Military Nursing Research Training: Fundamentals of Survey Methodology (July 23-27)



Applied Data Science: Managing Research Data for Re-Use (July 23-27)



The National Black Election/Politics Studies: Use and Analysis (July 30-August 3)



Assessing and Mitigating Disclosure Risk: Essentials for Social Scientists (July 30-August 3)



Providing Social Science Data Services: Strategies for Design and Operation (August 6-10)



Early Care and Education Policy: Drawing Lessons from Weighted Samples (TBD)