Dexin Shi

Assistant Professor

University of South Carolina

United States

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About

Dexin Shi is an Assistant Professor at the University of South Carolina in the United States. His research interests include statistical methodologies in psychological assessment, particularly focusing on model validation, measurement error, and causal inference. Recent articles highlight his work on the Root Mean Square Error of Approximation in non-normal data, the use of machine learning for equating in small samples, and the evaluation of response formats in clinical assessments.

Articles (15)

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2025

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2023

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2023

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2023

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2022

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2022

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2022

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2022

Collaborators (8)

Haiyan Liu

Assistant Professior

University of California Merced

UNITED STATES

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Ren Liu

Assistant Professor

University of California Merced

UNITED STATES

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Xu Jiang

UNITED STATES

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Jihong Zhang

Iowa State University

UNITED STATES

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Bo Zhang

Assistant Professor

University of Illinois at Urbana-Champaign

UNITED STATES

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Alberto Maydeu-Olivares

Professor

University of South Carolina

UNITED STATES

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Dingjing Shi

Assistant Professor

University of Oklahoma

UNITED STATES

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Amanda J. Fairchild

University of South Carolina

UNITED STATES

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Dexin Shi

Research Interests

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About

Articles (15)

Estimating the Root Mean Square Error of Approximation (RMSEA) with Multiply Imputed Data Under Non-Normality

Testing the validity of instrumental variables in just‐identified linear non‐Gaussian models

Comparing Likert and Slider Response Formats in Clinical Assessment: Evidence From Measuring Depression Symptoms Using CES-D 8

Distinguishing cause from effect in psychological research: An independence‐based approach under linear non‐Gaussian models

Evaluating Close Fit in Ordinal Factor Analysis Models With Multiply Imputed Data

The NEAT Equating Via Chaining Random Forests in the Context of Small Sample Sizes: A Machine-Learning Method

Is the Area Under Curve Appropriate for Evaluating the Fit of Psychometric Models?

The Effect of Model Size on the Root Mean Square Error of Approximation (RMSEA): The Nonnormal Case

Variable Selection for Mediators under a Bayesian Mediation Model

Factor Structure of the Teacher Strengths and Difficulties Questionnaire in a Large Community-Based Sample: An Investigation of Alternative Measurement Models

One step at a time: A statistical approach for distinguishing mediators, confounders, and colliders using direction dependence analysis.

Asymptotic is Better than Bollen-Stine Bootstrapping to Assess Model Fit: The Effect of Model Size on the Chi-Square Statistic

A Monte Carlo Study of Confidence Interval Methods for Generalizability Coefficient

Examining the validity and measurement invariance across gender and race of the Implicit Thoughts, Emotion, and Behavior Questionnaire.

Poisson Diagnostic Classification Models: A Framework and an Exploratory Example

Collaborators (8)

Haiyan Liu

Ren Liu

Xu Jiang

Jihong Zhang

Bo Zhang

Alberto Maydeu-Olivares

Dingjing Shi

Amanda J. Fairchild

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