Yale Quan

Yale Quan

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

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://https://doi.org/10.5964/meth.14303

  2. Parker, M., Ciou, S.Y., Quan, Y., Ren, H., Wang, C., & Li, M. (2025) Investigating Answer Choice Bias within a College-Level Introductory Computing Assessment. SIGCSE 2026. https://doi.org/10.1145/3770762.3772622

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

  4. 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.

  5. 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

  6. 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.

  7. 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

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. 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

  13. 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

  14. 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.

  15. 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

  16. 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

  17. 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) Using Multi-label Classification Neural Networks to Detect Intersectional DIF with Small Sample Sizes. British Journal of Mathematical and Statistical Psychology

  2. Wang, C., Quan, Y., Arthur, D. (Under Review) Review of Cognitive Diagnostic Models (CDMs): Recent Methodological Advancements for Addressing Challenges in Applications. British Journal of Mathematical and Statistical Psychology

  3. Quan, Y., & Wang, C. (In Preparation) Transitive DIF Clustering: A Graph-Theoretic Approach to Identifying Many-Group Partial Measurement Invariance. Psychological Methods

  4. 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