Does Acquiescence Disagree with Measurement Invariance Testing?

被引:1
|
作者
D'Urso, E. Damiano [1 ]
Tijmstra, Jesper [1 ]
Vermunt, Jeroen K. [1 ]
De Roover, Kim [1 ,2 ]
机构
[1] Tilburg Univ, Tilburg, Netherlands
[2] Katholieke Univ Leuven, Leuven, Belgium
关键词
Acquiescence response style (ARS); measurement invariance (MI); multiple group categorical confirmatory factor analysis (MG-CCFA); psychometrics; GOODNESS-OF-FIT; CONFIRMATORY FACTOR-ANALYSIS; RESPONSE STYLES; MODELING ACQUIESCENCE; EQUIVALENCE; EXTREME; BIAS; CONSEQUENCES; INDEXES;
D O I
10.1080/10705511.2023.2260106
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
Measurement invariance (MI) is required for validly comparing latent constructs measured by multiple ordinal self-report items. Non-invariances may occur when disregarding (group differences in) an acquiescence response style (ARS; an agreeing tendency regardless of item content). If non-invariance results solely from neglecting ARS, one should not worry about scale inequivalences but model the ARS instead. In a simulation study, we investigated the effect of ARS on MI testing, both when including ARS as a factor in the measurement model or not. For (semi-) balanced scales, disregarding a large ARS resulted in non-invariance already at the configural level. This was resolved by including an ARS factor for all groups. For unbalanced scales, disregarding ARS did not affect MI testing, and including an ARS factor often resulted in non-convergence. Implications and recommendations for applied research are discussed.
引用
收藏
页码:511 / 525
页数:15
相关论文
共 50 条
  • [1] Controlling acquiescence bias in measurement invariance tests
    Aichholzer, Julian
    PSIHOLOGIJA, 2015, 48 (04) : 409 - 429
  • [2] The Dire Disregard of Measurement Invariance Testing in Psychological Science
    Maassen, Esther
    D'Urso, E. Damiano
    van Assen, Marcel A. L. M.
    Nuijten, Michele B.
    De Roover, Kim
    Wicherts, Jelte M.
    PSYCHOLOGICAL METHODS, 2023,
  • [3] A Direct Comparison Approach for Testing Measurement Invariance
    Cheung, Gordon W.
    Lau, Rebecca S.
    ORGANIZATIONAL RESEARCH METHODS, 2012, 15 (02) : 167 - 198
  • [4] Measurement Invariance Testing Works
    Lasker, Jordan
    APPLIED PSYCHOLOGICAL MEASUREMENT, 2024, 48 (06) : 257 - 275
  • [5] A checklist for testing measurement invariance
    van de Schoot, Rens
    Lugtig, Peter
    Hox, Joop
    EUROPEAN JOURNAL OF DEVELOPMENTAL PSYCHOLOGY, 2012, 9 (04) : 486 - 492
  • [6] Invariance: What Does Measurement Invariance Allow Us to Claim?
    Protzko, John
    EDUCATIONAL AND PSYCHOLOGICAL MEASUREMENT, 2024,
  • [7] Measurement Invariance Testing with Many Groups: A Comparison of Five Approaches
    Kim, Eun Sook
    Cao, Chunhua
    Wang, Yan
    Nguyen, Diep T.
    STRUCTURAL EQUATION MODELING-A MULTIDISCIPLINARY JOURNAL, 2017, 24 (04) : 524 - 544
  • [8] A Monte Carlo Confidence Interval Method for Testing Measurement Invariance
    Li, Hui
    Liu, Hongyun
    STRUCTURAL EQUATION MODELING-A MULTIDISCIPLINARY JOURNAL, 2022, 29 (04) : 600 - 610
  • [9] Correction for measurement error in invariance testing: An illustration using SQP
    Pirralha, Andre
    Weber, Wiebke
    PLOS ONE, 2020, 15 (10):
  • [10] Evaluating Equivalence Testing Methods for Measurement Invariance
    Counsell, Alyssa
    Cribbie, Robert A.
    Flora, David B.
    MULTIVARIATE BEHAVIORAL RESEARCH, 2020, 55 (02) : 312 - 328