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

被引:0
|
作者
Zhang, Bo [1 ,2 ]
Chalmers, R. Philip [3 ]
Li, Lingyue [2 ]
Sun, Tianjun [4 ]
Tay, Louis [5 ]
机构
[1] Univ Illinois, Sch Lab & Employment Relat, 504 Armory, Champaign, IL 61820 USA
[2] Univ Illinois, Dept Psychol, 504 Armory, Champaign, IL 61820 USA
[3] York Univ, Dept Psychol, Toronto, ON, Canada
[4] Rice Univ, Dept Psychol Sci, Houston, TX USA
[5] Purdue Univ, Dept Psychol Sci, W Lafayette, IN USA
关键词
item response process; MixDUM; model selection; item response theory; LATENT TRAIT MODEL; CURVILINEAR RELATIONSHIPS; PARAMETER-ESTIMATION; JOB-PERFORMANCE; PERSONALITY; TOO; ASSUMPTIONS; THURSTONE; PATTERN; TALENT;
D O I
10.1177/10944281241271323
中图分类号
B849 [应用心理学];
学科分类号
040203 ;
摘要
When modeling responses to items measuring non-cognitive constructs that require introspection (e.g., personality, attitude), most studies have assumed that respondents follow the same item response process-either a dominance or an unfolding one. Nevertheless, the results are not equivocal, as some preliminary evidence suggests that some people use an unfolding response process, whereas others use a dominance response process. To enhance item response modeling, it is critical to develop measurement models that can accommodate heterogeneity in the item response processes. Therefore, we proposed the Mixture Dominance-Unfolding Model (MixDUM) to formally identify this potential population heterogeneity. Monte Carlo simulations showed that MixDUM possessed reasonably good statistical properties. Moreover, ignoring item response process heterogeneity was detrimental to item parameter estimation and led to less accurate selection outcomes. An empirical study was conducted in which respondents completed focal personality scales under either an honest condition or a simulated job application condition, to demonstrate the utility of MixDUM. The findings indicated (1) that MixDUM provided the best fit across scales, (2) that approximately 55-60% of respondents utilized an unfolding response process, (3) that respondents exhibited moderate consistency in their use of response processes across scales, (4) that narcissism consistently negatively predicted the use of an unfolding response process, and (5) that the criterion-related validity of focal personality scores varied across latent classes for certain criteria. To encourage its use, we provided a tutorial on the implementation of MixDUM in the R package mirt.
引用
收藏
页数:41
相关论文
共 50 条
  • [31] Treatment of the modal patient: Does one size fit nearly all? Editor's response
    Kellner, CH
    JOURNAL OF ECT, 2001, 17 (03) : 221 - 222
  • [32] Response to: One size does not fit all-application of accelerometer thresholds in chronic disease
    Barker, Joseph
    Byrne, Karl Smith
    Doherty, Aiden
    Foster, Charlie
    Rahimi, Kazem
    Ramakrishnan, Rema
    Woodward, Mark
    Dwyer, Terence
    INTERNATIONAL JOURNAL OF EPIDEMIOLOGY, 2019, 48 (04) : 1381 - 1381
  • [33] One size does not fit all. Business models heterogeneity among Internet of Things architecture layers
    Del Sarto, Nicola
    Cesaroni, Fabrizio
    Di Minin, Alberto
    Piccaluga, Andrea
    TECHNOLOGY ANALYSIS & STRATEGIC MANAGEMENT, 2022, 34 (07) : 787 - 802
  • [34] Batch-to-Batch Variation and Patient Heterogeneity in Thymoglobulin Binding and Specificity: One Size Does Not Fit All
    den Hollander, Nicoline H. M.
    Jansen, Diahann T. S. L.
    Roep, Bart O.
    JOURNAL OF CLINICAL MEDICINE, 2025, 14 (02)
  • [35] One-size-does-not-fit-all: A Case for Further Research on the Tenets of the Trust Model
    Eneli, Ihuoma U.
    Crum, Peggy
    Tylka, Tracy L.
    OBESITY, 2009, 17 (08) : 1478 - 1480
  • [36] One Size Does Not Fit All: Applying the Transtheoretical Model to Energy Feedback Technology Design
    He, Helen Ai
    Greenberg, Saul
    Huang, Elaine M.
    CHI2010: PROCEEDINGS OF THE 28TH ANNUAL CHI CONFERENCE ON HUMAN FACTORS IN COMPUTING SYSTEMS, VOLS 1-4, 2010, : 927 - 936
  • [37] One size does not fit all ... panel data: Bayesian model averaging and data poolability
    Desbordes, Rodolphe
    Koop, Gary
    Vicard, Vincent
    ECONOMIC MODELLING, 2018, 75 : 364 - 376
  • [38] One size does not fit all: Optimizing size-inclusive model photography mitigates fit risk in online fashion retailing
    Zhang, Yerong
    Ikonen, Iina
    Eelen, Jiska
    Sotgiu, Francesca
    JOURNAL OF THE ACADEMY OF MARKETING SCIENCE, 2024,
  • [39] Using Stretch Goals for Idea Generation Among Employees: One Size Does Not Fit All!
    Ahmadi, Saeedeh
    Jansen, Justin J. P.
    Eggers, J. P.
    ORGANIZATION SCIENCE, 2022, 33 (02) : 671 - 687
  • [40] One size does not fit all: Customizing MCMC methods for hierarchical models using NIMBLE
    Ponisio, Lauren C.
    de Valpine, Perry
    Michaud, Nicholas
    Turek, Daniel
    ECOLOGY AND EVOLUTION, 2020, 10 (05): : 2385 - 2416