February 5, 2014

12TH Annual “Stats Camp”

The Institute for Measurement, Methodology, Analysis and Policy (Todd D. Little, director) at TEXAS TECH UNIVERSITY is proud to announce the 12TH Annual “Stats Camp”

June 2-6 & 9-13, 2014 ● 9:00 a.m. - 5:00 p.m.
Holiday Inn Convention Center ● Lawrence, Kansas

June 2 – 6, 2014:
1. Structural Equation Modeling: Foundations and Extended Applications (Todd D. Little & Noel A. Card, instructors)
Topics include confirmatory factor analysis, multiple-group comparisons, factorial invariance as well as 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.
2. Applied Latent Class Analysis and Finite Mixture Modeling (Katherine Masyn, instructor)
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.
3. Multilevel Modeling: Foundations and Applications (James P. Selig, instructor)
The theory and practice of methods for analyzing hierarchically organized data. Topics include random effects, centering, multiparameter tests, plotting cross-level interactions, and other applications of multilevel modeling, including multilevel SEM.
4. Item Response Theory (William P. Skorupski, instructor)
Theoretical and practical advantages of scaling assessment data using IRT. Introduction to various IRT models and their applications, including software training and opportunities for students to analyze their own data.

June 9 – 13, 2014:
5. Longitudinal Structural Equation Modeling (Todd D. Little, instructor)
Topics will include design and measurement issues in longitudinal research, traditional panel designs, latent growth curve analysis, as well as a brief survey of advance growth mixture modeling, multi-level SEM with longitudinal data and dynamic intra-individual modeling.
6. Foundations of Meta-Analysis (Noel A. Card, instructor)
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.
7. Social Network Analysis with Siena (Leslie Echols, instructor)
Introduction to social network analysis for exponential random graph models (ERGM; cross-sectional networks) and longitudinal networks using R and RSiena. With a focus on actor-oriented and tie-oriented characteristics of and changes within complete social networks, the course will survey a variety of approaches to analyzing network data at single or multiple points in time.
8. Mediation and Moderation: Modern Methods and Approaches (Alexander Schoemann, instructor)
Classic and contemporary approaches to estimating moderation and mediation effects; topics include path analysis, indirect and direct effects, testing intervening variable effects, probing and plotting interactions, and combining moderation and mediation.
9. Structural Equation Modeling and Data Analysis with Mplus (Rens van de Schoot, instructor)
Course includes introduction to SEM using Mplus ; advanced models (e.g., growth curve models and Latent Class modeling) and Bayesian statistics. Morning lectures are followed by afternoon computer lab activities with Mplus.


Register by April 30 and receive an early bird discount on the institute fee.
Sign up for consecutive courses and receive a discount to offset the weekend hotel costs.
These training institutes are offered every year in June. Go to statscamp.org for ongoing information and to sign up.

*For all courses Friday afternoons are reserved for consulting on projects and participants are welcome to depart for travel.*

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