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Matthew Naveiras


Research Area: Quantitative Methods

Representative Publications

Methodological Papers in Peer-Reviewed Journals  
  • Cho, S.-J., Shen, J., & Naveiras, M. (2019). Multilevel reliability measures of latent scores within an item response theory frameworkMultivariate Behavioral Research, 54, 856-881.
  • Cho, S.-J., Naveiras, M., & Barton, E. E. (in press). Modeling multivariate count time series data with a vector Poisson log-normal additive model: Applications to testing intervention effects in single-case designs. Multivariate Behavioral Research.
  • Cho, S.-J., Watson, D. G., Jacobs, C., & Naveiras, M. (in press). A Markov mixed-effect multinomial logistic regression model for nominal repeated measures: An analysis on syntactic self-priming effects. Multivariate Behavioral Research.

Journal/Book Chapters

  • Brown-Schmidt, S., Cho, S.-J., De Boeck, P., & Naveiras, M. (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). [Funding was supported in part by the National Science Foundation (SES 1851690)]
  • Cho, S.-J., Brown-Schmidt, S., Naveiras, M., & De Boeck, P. (2020). A dynamic generalized mixed effect model for intensive binary temporal-spatio data from an eye tracking technique. In H. Jao & R.W. Lissitz (Eds.), Innovative psychometric modeling and methods (pp. 45-68). Charlotte, NC: Information Age Publishing.

Conference Presentations

  • Naveiras, M., & Cho, S.-J. (2020). Using auxiliary item information in the item parameter estimation of a graded response model. Poster presented at annual Meeting of National Council on Measurement in Education (NCME), virtual.
  • Naveiras, M., Cho, S.-J., & Shen, J. (2020). Multilevel reliability measures of latent scores within an item response theory framework. Paper presented at annual Meeting of National Council on Measurement in Education (NCME), virtual.
  • Naveiras, M., Cho, S.-J., De Boeck, P., & Brown-Schmidt, S. (2020). A dynamic tree-based item response model. Poster presented at the International Meeting of Psychometric Society, College Park, MD.
  • Brown-Schmidt, S., Naveiras, M., Cho, S.-J., & De Boeck, P. (2021). A dynamic tree-based item response model for visual world eye-tracking data. Paper presented at the 34th annual CUNY conference on human sentence processing.
  • Naveiras, M., Cho, S.-J., Goodwin, A.P., & Salas, J.A. (2021, June). Analysis of digital reading processes from multimodal time-series data using deep learning. Paper to be presented at annual Meeting of National Council on Measurement in Education (NCME), virtual.

Web Materials

  • Naveiras, M., & Cho, S.-J. (2020). Tutorial: Fitting dynamic tree-based item response models to intensive polytomous time series eye-tracking data using R. https://naveirmd.github.io/IRTree-Tutorial/