Post Conference Workshop:
Item Response Theory and Modeling: A Latent Variable Modeling Approach
May 24, 2018
Michigan State University
This one-day workshop is based on a latent variable modeling approach to item response theory (IRT) and item response modeling (IRM). The workshop commences with a non-traditional approach to IRT and IRM that is based on their essential connections to other behavioral measurement methodologies. These include classical test theory (CTT), (nonlinear) factor analysis, and logistic regression. The flaws of earlier treatments of CTT in the context of multiple IRT and IRM discussions are pointed out, which in addition to misrepresenting CTT effectively shift away research attention to more specific rather than more generally applicable modeling and analytic procedures. Resent research on the connections between classical test theory and IRT/IRM is then reviewed. Using a measurement invariance examination based approach, a multiple testing method for differential item functioning is discussed that deals with limitations of an existing widely utilized procedure. A readily applicable method for studying essential unidimensionality of multi-item measuring instruments is then obtained as a byproduct of this method. Item response models with covariates are finally discussed. Use of the popular software Mplus and Stata is made repeatedly and on a few occasions IRTPRO, flexMIRT, and R are utilized. The workshop is based on an integrative approach to measurement in the behavioral and social sciences and emphasizes throughout the links between IRT and IRM on the one hand and other measurement and modeling methodologies related to them on the other hand.
This workshop will be held on Thursday, May 24, 2018 from 8:30-4:30pm in Laurel Hall, Room 102.
Raykov, T., & Marcoulides, G. A. (2017). A course in item response theory and modeling with Stata. College Station, TX: Stata Press.
Raykov, T., & Marcoulides, G. A. (2016). On the relationship between classical test theory and item response theory: From one to the other and back. Educational and Psychological Measurement, 76, 325-338.
Raykov, T., & Marcoulides, G. A. (2017). On studying common factor dominance and approximate unidimensionality in multi-component measuring instruments with discrete items. Educational and Psychological Measurement (in press).
Register for the post-conference or the 2018 Modern Modeling Methods Conference, click here.