Bo Zhang

Assistant Professor

University of Illinois at Urbana-Champaign

United States

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About

Bo Zhang is an Assistant Professor at the University of Illinois Urbana-Champaign. His research areas include item response theory, psychological measurement, and the dynamics of resilience in work environments. Zhang has published extensively, contributing to topics such as the validation of psychological inventories across cultures and the modeling of forced-choice data. His recent work focuses on unraveling item response process heterogeneity and examining the impacts of contextualization strategies on measurement validity.

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Collaborators (9)

Dexin Shi

Assistant Professor

University of South Carolina

UNITED STATES

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Nicholas Turiano

Associate Professor

West Virginia University

UNITED STATES

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Ren Liu

Assistant Professor

University of California Merced

UNITED STATES

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Tianjun Sun

Assistant Professor

Rice University

UNITED STATES

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Seonghee Cho

Associate Professor

Sungkyunkwan University

SOUTH KOREA

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Daniel Mroczek

Professor

Northwestern University

UNITED STATES

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Young Woo Sohn

Professor

Yonsei University

SOUTH KOREA

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Charles C. Driver

University of Zurich

SWITZERLAND

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Louis Tay

Professor

Purdue University

UNITED STATES

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Bo Zhang

Research Interests

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About

Articles (20)

One Size Does Not Fit All: Unraveling Item Response Process Heterogeneity Using the Mixture Dominance-Unfolding Model (MixDUM)

The Big Five Inventory-2 in Korea: Validation and Cross-Cultural Comparisons with the U.S. and Chinese Versions

What is common may be as important as what is different: Examining the general factor shared by dispositional shame and guilt using bi-factor models

The More Contextualized, the More Valid: Effects of Contextualization Strategies on Forced-choice Measurement

A Structural After Measurement Approach to Bifactor Predictive Models

Clarifying the Construct of Supervisor Support for Recovery and Its Impact on Employee Recovery Experiences

Mixed-Keying or Desirability-Matching in the Construction of Forced-Choice Measures? An Empirical Investigation and Practical Recommendations

Killing Two Birds with One Stone: Accounting for Unfolding Item Response Process and Response Styles Using Unfolding Item Response Tree Models

The role of resilience in navigating work stress and achieving daily work goals

Moving beyond Likert and Traditional Forced-Choice Scales: A Comprehensive Investigation of the Graded Forced-Choice Format

How well can an AI chatbot infer personality? Examining psychometric properties of machine-inferred personality scores.

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

Small but Nontrivial: A Comparison of Six Strategies to Handle Cross-Loadings in Bifactor Predictive Models

The Generalized Thurstonian Unfolding Model (GTUM): Advancing the Modeling of Forced-Choice Data

The effects of socioeconomic status on personality development in adulthood and aging

Directionality in the interrelations between approximate number, verbal number, and mathematics in preschool‐aged children

The Stressful Personality: A Meta-Analytical Review of the Relation Between Personality and Stress

Faking Detection Improved: Adopting a Likert Item Response Process Tree Model

Personality and health: Disentangling their between-person and within-person relationship in three longitudinal studies.

autoFC: An R Package for Automatic Item Pairing in Forced-Choice Test Construction

Collaborators (9)

Dexin Shi

Nicholas Turiano

Ren Liu

Tianjun Sun

Seonghee Cho

Daniel Mroczek

Young Woo Sohn

Charles C. Driver

Louis Tay

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