Yale Quan

Yale Quan

Ph.D. student in Measurement & Statistics at University of Washington Seattle.

Publications and Presentations

PRESENTATIONS AND PUBLICATIONS

  1. Quan, Y., & Wang, C. (2025). Collapsing or Not? A Practical Guide to Handling Sparse Responses for Polytomous Items. Methodology, 21(1), 46-73. https://doi.org/10.5964/meth.14303

  2. Parker, M., Ciou, S.Y., Quan, Y., Ren, H., Wang, C., & Li, M. (In Press) Investigating Answer Choice Bias within a College-Level Introductory Computing Assessment. SIGCSE 2026

  3. Quan, Y., & Wang. C. (2025, July 15-18) A Neural Network Approach to Small Sample Intersectional DIF Detection [Paper Presentation]. Annual International Meeting of the Psychometric Society (IMPS), Minneapolis, MN, USA.

  4. Quan, Y. (2025, May 9) Using Categorical Structural Equation Models to Identify Facets of Student Belonging [Paper Presentation]. Community Partner Doctoral Fellowship Research Presentation, Seattle, WA, United States

  5. Quan, Y., Ren, H., & Wang, C. (2025, March 29) Constructing A Machine Learning Model For Binary Predictions with Incomplete, Imbalanced Data and Non-Linear Effects [Paper Presentation]. A Meeting of Methodologists.

  6. Quan, Y., Sager, M. (2025, February 17-20) Identifying Core Formal Assessment Competencies and Informal Learning Outcomes of Data Science and Data Literacy [Paper Presentation]. Data Science Education K-12: Research to Practice Annual Conference

  7. Quan, Y., & Ren, H. (2024, December 4) Sample Size and Test Length Recommendations for the Diagnostic Facet Status Model [Paper Presentation]. Center for Statistics and The Social Sciences Student Research Presentation, Seattle, WA, United States.

  8. Quan, Y., & Wang, C. (2024, November 17-18) A New Item Fit Test for the Diagnostic Facet Test Model (DFSM) [Paper Presentation]. Annual Pacific Northwest Research on Psychometrics and Applied Statistics Conference, Pullman, WA, United States.

  9. Quan, Y. (2024, June 4) Introduction to Bayesian Item Response Theory[Paper Presentation]. Center for Statistics and The Social Sciences Student Research Presentation, Seattle, WA, United Sates.

  10. Quan, Y. (2024, October 18) Item Response Theory (IRT) Model Selection and Applications [Invited Talk]. University of Washington Behavioral Research Center for HIV, Seattle, WA, United States.

  11. Quan, Y., & Wang, C. (2024, April 11-14) Parameter Recovery from Higher Order Item Response Theory Models with Structural Missingness [Paper Presentation]. National Council on Measurement in Education 2024 Annual Meeting, Philadelphia, PA, United States

  12. Quan, Y., & Wang, C. (2024, April 11-14) Collapsing or not? A Practical Guide to Handling Sparse Responses for Polytomous Items [Poster Presentation, Paper Presentation], American Educational Research Association Annual Meeting, Philadelphia, PA, United States. https://doi.org/10.3102/2102869

  13. Quan, Y., & Xiao, T. (2024, March 11) The Effects of Measurement Error on Multilevel Linear Growth Model Parameter Estimates, [Paper Presentation]. Center for Statistics and The Social Sciences Student Research Presentation, Seattle, WA, United States.

  14. Quan, Y., & Wang, C. (2022, April 12-15) The Effects of Sample Size and Collapse Direction on Parameter Recovery [Poster Presentation]. National Council on Measurement in Education 2023 Annual Meeting, Chicago, IL, United States

  15. Quan, Y. (2021, December 3). Clustering Education Data Using K-Medoids with Partitioning Around the Medoids Algorithm [Seminar Presentation]. Measurement & Statistics Seminar, University of Washington. Seattle, WA, United States

  16. Quan, Y. (2020). A Multivariate Statistical Analysis of Major Change Patterns and Significant Factors That Influence Graduation Rates: A Case Study at California State University, Long Beach (Publication No. 28155286) [Master’s Thesis, California State University Long Beach]. ProQuest Dissertations and Theses Global. https://www.proquest.com/dissertations-theses/multivariate-statistical-analysis-major-change/docview/2519029245/se-2

PREPRINT MANUSCRIPTS

  1. Quan, Y., & Wang, C. (2025). Using Multi-label Classification Neural Network to Detect Intersectional DIF with Small Sample Sizes. PsyArXiv. https://doi.org/10.31234/osf.io/rftyg_v2

  2. Quan, Y., & Ren, H. (2025). Sample Size and Assessment Length Recommendations for the Diagnostic Status Facet Model. PsyArXiv. https://doi.org/10.31234/osf.io/zr3je_v1

MANUSCRIPTS UNDER REVIEW AND IN PREPERATION

  1. Quan, Y., & Wang, C. (Under Review) Calibrating Multidimensional Assessments with Structural Missingness, An Application of a Multiple-Group Higher-Order IRT Model. Applied Psychological Methods*

  2. Quan, Y., & Wang, C. (Under Review) Using Multi-label Classification Neural Networks to Detect Intersectional DIF with Small Sample Sizes. British Journal of Mathematical and Statistical Psychology

  3. Park, A., Quan, Y., Lohr, M., & Oxford, M. (In Preparation). Concurrent and enduring predictors of preschool language among young children of parents involved in child welfare. Journal of Speech, Language, and Hearing Research