Please join us for one of two pre-conference workshops on Wednesday, October 22nd, 10:00am-12:45pm
1. An Introduction to Structural Equation Modeling
2. Introductory R Workshop
An Introduction to Structural Equation Modeling
, Professor, James Madison University
, Doctoral Student, James Madison University
The purpose of the training session is to provide attendees with a general overview of structural equation modeling (SEM) by introducing path analysis, confirmatory factor analysis (CFA), and full structural equation modeling. We will start with path analysis, which models relationships among measured variables, then move to CFA, which is simply an extension of exploratory factor analysis, and finish with full structural models involving latent variables, which essentially merges path analysis and CFA. The advantage of the latter is that theories may be tested by estimating relationships between the underlying constructs of interest, rather than estimating relationships between observed variables that are contaminated by measurement error. Links will be made between these techniques and other more familiar techniques such as multiple regression and exploratory factor analysis. For each SEM technique, the following steps in the analysis process will be explained: model specification, model identification, model-data fit evaluation, and parameter estimate interpretation. This 3-hour workshop requires no prior experience with SEM.
About the Facilitators
Dr. Sara Finney has a dual appointment at James Madison University (JMU) as a Professor in the Department of Graduate Psychology and as a Senior Assessment Specialist in the Center for Assessment and Research Studies, where she teaches courses in structural equation modeling and multivariate statistics. In addition to serving as a faculty member for the Assessment and Measurement Ph.D. program, Dr. Finney coordinates the Quantitative Psychology Concentration within the Psychological Sciences M.A. program at JMU. Much of her research involves the application of structural equation modeling techniques to assess the functioning of self-report measures.
Kelly Foelber is a second-year student in JMU’s Assessment and Measurement Ph.D. program, as well as a Graduate Assistant for JMU’s Center for Assessment and Research Studies. Kelly graduated from JMU’s Psychological Sciences M.A. program in 2014, and from Franklin and Marshall College in 2011.
Introductory R Workshop
, Associate Research Scientist, Educational Testing Service
The basics of data manipulation, statistical functions, and graphs will be covered, including: Basic R commands, accessing help and documentation, importing data, descriptive statistics, significance tests, and creating graphs in base R. No prior knowledge is assumed.
About the Facilitator
Jonathan Weeks is an Associate Research Scientist in the Research & Development Division at Educational Testing Service. He recently received a Ph.D. in Research and Evaluation Methodology from the University of Colorado at Boulder. He has written an R package for IRT-based test linking that is now one of the core psychometric packages. He has published in various peer-reviewed journals including the Journal of Educational and Behavioral Statistics, Educational Measurement: Issues and Practices, and the Journal of Statistical Software. His current research focuses on the development of multidimensional vertical scales and the identification of between-test dimensionality when the construct of interest changes over time.