Research | Che Cheng

How do we represent choice?

This fundamental question drives my research program. When people make choices or express preferences, what mathematical framework best captures the underlying psychological process?

For a complete list of publications, see my CV or ORCID profile.

Research Lines

Quantitative Methods

Joint Thurstonian Models — Integrating Likert scales and comparative judgment
Toward Optimal Estimation — Identifiability, efficiency, and finite-sample properties
Psychophysics & Adaptive Methods — Threshold estimation with response confidence
Sample Size Planning — Integrating power analysis and estimation precision
Effect Size Methods — Quantifying treatment effects in single-case designs

Developmental & Applied

Predetermined R² — Quantifying developmental determinism
Growth Curve Modeling — Semiparametric developmental trajectories
Mastery Motivation & Parenting — Parental influences on motivational development
Academic Motivation & Self-regulation — Procrastination, helplessness, and fear of failure
Applied Quantitative Research — Interdisciplinary statistical consulting

Highlighted Streams

1. Measurement Paradigm Unification

Central Question: When we measure preferences using different methods, are we measuring the same construct?

Different measurement paradigms exist in psychology:

Paradigm	Example	Data Type
Likert scale	"Rate your agreement 1-7"	Ordinal ratings
Pairwise comparison (comparative judgment)	"Which do you prefer, A or B?"	Binary choices
Ranking	"Rank these 5 items"	Ordinal ranks
Q-sort	"Sort cards into piles"	Forced distribution

My research investigates the theoretical conditions under which these methods yield equivalent conclusions.

Selected Publications

Cheng, C., Lay, K.-L., Hsu, Y.-F., & Tsai, Y.-M. (2021). Can likert scales predict choices?: Testing the congruence between using likert scale and comparative judgment on measuring attribution. Methods in Psychology, 5, Article 100081. https://doi.org/10.1016/j.metip.2021.100081

2. Statistical Foundations

Central Question: What are the identifiability conditions for psychometric models?

Before we can trust parameter estimates, we must establish that the model is mathematically identified—that there exists a unique solution.

Key contributions:

Necessary and sufficient conditions for polychoric model identifiability
Implications for ordinal SEM and item factor analysis

Selected Publications

Cheng, C., Yang, H.-H., & Hsu, Y.-F. (2025). Identifiability of polychoric models with latent elliptical distributions. Psychometrika, 90(2), 757–778. https://doi.org/10.1017/psy.2024.25 Professor Chao-ming Cheng Memorial Scholarship

Cheng, C., Huang, Y.-J., & Hsu, Y.-F. (2022). Incorporating response confidence into adaptive methods for threshold estimation. Chinese Journal of Psychology, 64(2), 217–232. https://doi.org/10.6129/cjp.202206_64(2).0005 * Equal contribution

3. Practical Applications

Central Question: How should researchers choose between measurement paradigms?

Beyond theoretical equivalence, practical considerations matter:

Response burden
Cognitive demands
Reliability and precision
Susceptibility to biases

Selected Publications

Chen, Y.-K., Yang, T.-R., Chen, L.-T., Hsieh, C.-Y., Cheng, C., Wu, P.-J., & Peng, C.-Y. J. (2025). Improving applications of a design-comparable effect size in single-case designs. Behavior Research Methods, 57(10), Article 279. https://doi.org/10.3758/s13428-025-02715-1

Chen, L.-T., Chen, Y.-K., Yang, T.-R., Chiang, Y.-S., Hsieh, C.-Y., Cheng, C., Ding, Q.-W., Wu, P.-J., & Peng, C.-Y. J. (2024). Examining the normality assumption of a design-comparable effect size in single-case designs. Behavior Research Methods, 56(1), 379–405. https://doi.org/10.3758/s13428-022-02035-8

Theoretical Framework

Thurstonian Models / Random Utility Theory

My work builds on Thurstonian models as a unifying framework:

Key insight: All these measurement methods can be viewed as different "windows" into the same underlying latent utilities. The Thurstonian framework provides testable predictions about when methods should agree or disagree.

Research Grants

NSTC Doctoral Dissertation Award (2024–2025)

Title: 學業歸因種類與向度對於學習適應之預測力探討

National Science and Technology Council, Taiwan

Grant No. 113-2424-H-002-002-DR

College Student Research Scholarship (2015)

Title: 大學生拖延閒混的兩種亞型--短視近利型及意志軟弱型拖延閒混

Ministry of Science and Technology, Taiwan

Grant No. 104-2815-C-002-188-H

College Student Research Scholarship (2014)

Title: 從絕望中看見希望--探討數理資優生習得性無助背後的學習動機與家庭因素

Ministry of Science and Technology, Taiwan

Grant No. 103-2815-C-002-057-H