The Institute for Measurement, Methodology, Analysis, and Policy (IMMAP) at Texas Tech University is accepting registrations for the 12th Annual Stats Camp, to be held June 2–6 and 9–13 in Lawrence, Kansas.
Stats Camp is targeted toward graduate students, post-doctoral students, and professors. Students will have the chance to participate in specialized statistical training courses not offered at their universities and learn specific statistical techniques that can be used for a thesis or dissertation. Professors can learn new statistical methods and approaches, stay up-to-date on statistical methods and analytic software (MPlus, R, SAS), and diversify their “statistical toolbox.” The camp is also open to those who have questions about their own data and projects and are seeking statistical consultations.
Highlighted courses include the following:
Structural Equation Modeling: Foundations and Extended Applications
Instructors: Todd Little, Texas Tech University, and Noel Card, The University of Arizona
Topics include confirmatory factor analysis; multiple-group comparisons; factorial invariance; and extended applications such as hierarchical models, multi-level SEM, and multi-trait-multi-method analyses. Opportunities for personal consulting and hands-on practice are provided.
Applied Latent Class Analysis and Finite Mixture Modeling
Instructor: Katherine Masyn, Harvard University
An introduction to “person-centered” data analysis. Topics include latent class analysis, latent class cluster analysis, modeling predictors and outcomes of latent class membership, and select longitudinal extensions such as latent transition analysis. Hands-on practice with MPlus is provided.
Foundations of Meta-Analysis
Instructor: Noel Card, University of Connecticut
This course teaches the skills necessary to conduct and write publishable meta-analytic reviews, including methods of searching the empirical literature, coding effect sizes, and analyzing effect sizes across multiple studies.
Longitudinal Structural Equation Modeling
Instructor: Todd Little, Texas Tech University
Topics will include design and measurement issues in longitudinal research; traditional panel designs; latent growth curve analysis; and a brief survey of advance growth mixture modeling, multi-level SEM with longitudinal data, and dynamic intra-individual modeling.
Visit their website for more information or to register.
I went to Stats Camp in the summer of 2013, and it was the best compressed stats training I have had yet! The instructor was extremely clear, gave alternatives to common statistical techniques, as well as discussed the pros and cons of different theoretical and practical approaches. The materials and examples were superb. The quantitative graduate students and course assistant were very knowledgeable as well as helpful one-on-one or through email. Like I said, this was a great experience.
Stats Camp Rocks!! Todd Little has a gift explaining the concepts of SEM. Wouldn’t have been able to finish my thesis without his SEM and Longitudinal SEM classes. Highly recommend!!