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Sun-Joo Cho

Associate Professor of Psychology and Human Development
Vanderbilt Data Science Institute & Data Science Minor Affiliate Faculty

Research topics include generalized latent variable models, generalized linear mixed-effects models, generalized additive models, and parameter estimation, with a focus on item response modeling.

Data complexity Dr. Cho has dealt with consists of (1) multiple manifest person categories such as a control group versus a treatment group in an experimental design, (2) multiple latent person categories (or mixtures or latent classes) such as a mastery group versus a non-mastery group in a cognitive test, (3) multiple item groups that may lead to multidimensionality such as number operation, measurement, and representation item groups in a math test, (4) multiple groups such as hospitals where patients are nested in a multilevel (or hierarchical) data structure, (5) repeated measures such as pretest and posttest in intervention studies, (6) intensive (many time points) binary, ordinal, nominal, and count time series (e.g., from eye-tracking, fMRI, emotional responses, dynamic treatment regimes, and N-of-1 or single case trials), (7) response processes (e.g., multinomial processing), (8) spatial dependence, (9) multiple sequences (channels), and (10) nonlinear interactions.

Dr. Cho has collaborated with researchers from a wide variety of disciplines including reading education, math education, special education, psycholinguistics, clinical psychology, cognitive psychology, neuropsychology, audiology, medicine, and computer science (artificial neural networks applications). She serves on the editorial boards of Behavior Research Methods, International Journal of Testing, Journal of Educational Measurement, and Psychologial Methods. She was also named a National Academy of Education/Spencer Postdoctoral Fellow (2013), a Vanderbilt Chancellor Faculty Fellow (2019-2021), and an Association for Psychological Science (APS) Fellow (Quantitative Field, 2020 - ). Dr. Cho has current research projects funded by the National Science Foundation (NSF) and the National Institutes of Health (NIH). 

Representative Publications

* denotes co-authors at Vanderbilt University.

Google Scholar, PubMed

Methodological Papers in Peer-Reviewed Journals  

- A tutorial on fitting a dynamic tree-based item response model using R (Laplace approximation) can be found here.  
- Stan code for Bayesian analysis can be found here.
- A poster presented at the (virtual) International Meeting of the Psychometric Soceity 2020 can be found here
- Researchers in substantive areas may be interested in reading the following book chapter to apply a dynamic tree-based item response model:
Brown-Schmidt, S.*, Naveiras, M.*, De Boeck, P., & Cho, S.-J. (2020). Statistical modeling of intensive categorical time series eye-tracking data using dynamic generalized linear mixed-effect models with crossed random effects. A special issue of "Gazing toward the future: Advances in eye movement theory and applications", Psychology of learning and motivation series (Volume 73).
- Some extensions of dynamic tree-based item response models are described in the following book chpater: 
De Boeck, P., & Cho, S.-J. (2020). IRTree modeling of cognitive processes based on outcome and intermediate data. In H. Jao & R. W. Lissitz (Eds.), Innovative psychometric modeling and methods (pp. 91-104). Charlotte, NC: Information Age Publishing. 

 

Substantive Papers in Peer-Reviewed Journals 

 

Book Chapters

 


Honors

  • Association for Psychological Science (APS) Fellow (2020)
  • Vanderbilt University Chancellor Faculty Fellow (2019-2021)
  • Vanderbilt University Provost Research Studios  (PRS) Award (2018)
  • Vanderbilt University Trans-Institutional Program (TIPs) Award (co-PI)  (2016-2018)

Study Title: Understanding digital dominance in teaching and learning: An interdisciplinary approach

  • Vanderbilt University Research Scholar Grant Award (2016)

Study Title: Multilevel reliability measures in a multilevel item response theory framework

Study Title: An application to simultaneous investigation of word and person contributions to word reading and lexical representations using random item response models

  • National Academy of Education/Spencer Postdoctoral Fellow (9/2013 - 6/2015)

Study Title: Evaluating educational programs with a new item response theory perspective 

  • National Council on Measurement in Education (NCME) Award for an Outstanding Example of an Application of Educational Measurement Technology to a Specific Problem (2011)

Study Title: Latent transition analysis with a mixture IRT measurement model

  •  State-of-the-Art Lecturer, Psychometric Society (2010)

Study Title: Random item response models