My research interests are in the development and application of item response theory (IRT) models to measure psychological constructs. Over the past two decades, I have developed a family of polytomous IRT models to unfold responses to test or questionnaire items. These unfolding models imply higher item scores to the extent that an individual is located close to an item on a unidimensional latent continuum. Unfolding item response models can be used to measure attitudes using responses from traditional Likert or Thurstone scales. They can also be used to assess satisfaction, preference, personality and individual differences in certain developmental processes that occur in distinct stages. My research and development efforts with unfolding IRT models have been recognized by the National Science Foundation via its Faculty Early Career Development (CAREER) Award, and the computer freeware spawned by this work (GGUM2004) has been used by researchers worldwide.
My current research extends these earlier unfolding models to the multidimensional domain where an individual is expected to endorse an item (or prefer a stimulus) to the extent that the individual is close to it in a latent space. These models have a host of dimensionality assessment and estimation issues that my students and I are investigating. Along with these new unfolding models, we are also developing alternative multidimensional models for change in longitudinal contexts where measurement invariance is not achieved, as well as hybrid multidimensional preference models based on external unfolding of previously scaled stimuli.
Ph.D. (1995) Experimental Psychology, Quantitative University of South Carolina
- Roberts, J. S., Laughlin, J. E., & Wedell, D. H. (1999). Validity issues in the Likert and Thurstone approaches to attitude measurement. Educational and Psychological Measurement, 59, 211-233.
- Roberts, J. S., Donoghue, J. R., & Laughlin, J. E. (2000). A general item response theory model for unfolding unidimensional polytomous responses. Applied Psychological Measurement, 24, 3-32.
- Roberts, J. S., Fang, H., Cui, W. And Wang, Y. (2006). GGUM2004: A Windows-based Program to Estimate Parameters in the Generalized Graded Unfolding Model. Applied Psychological Measurement, 30,64-65.
- Roberts, J. S. (2008). Modified likelihood-based item fit statistics for the generalized graded unfolding model. Applied Psychological Measurement 32, 407-423.
- Roberts, J. S., & Thompson, V. M. (2011). Marginal maximum a posteriori item parameter estimation for the generalized graded unfolding model. Applied Psychological Measurement, 35, 259-279.