864
Views
1
CrossRef citations to date
0
Altmetric
Research Articles

Does Acquiescence Disagree with Measurement Invariance Testing?

ORCID Icon, , &
Pages 511-525 | Received 07 Oct 2022, Accepted 13 Sep 2023, Published online: 02 Nov 2023

References

  • Aichholzer, J. (2015). Controlling acquiescence bias in measurement invariance tests. Psihologija, 48, 409–429. https://doi.org/10.2298/PSI1504409A
  • Arias, V. B., Garrido, L., Jenaro, C., Martínez-Molina, A., & Arias, B. (2020). A little garbage in, lots of garbage out: Assessing the impact of careless responding in personality survey data. Behavior Research Methods, 52, 2489–2505. https://doi.org/10.3758/s13428-020-01401-8
  • Austin, E. J., Deary, I. J., & Egan, V. (2006). Individual differences in response scale use: Mixed Rasch modelling of responses to neo-FFI items. Personality and Individual Differences, 40, 1235–1245. https://doi.org/10.1016/j.paid.2005.10.018
  • Bachman, J. G., & O'Malley, P. M. (1984). Yea-saying, nay-saying, and going to extremes: Black-white differences in response styles. Public Opinion Quarterly, 48, 491–509. https://doi.org/10.1086/268845
  • Bentler, P. M. (1990). Comparative fit indexes in structural models. Psychological Bulletin, 107, 238–246. https://doi.org/10.1037/0033-2909.107.2.238
  • Billiet, J. B., & McClendon, M. J. (2000). Modeling acquiescence in measurement models for two balanced sets of items. Structural Equation Modeling, 7, 608–628. https://doi.org/10.1207/S15328007SEM0704_5
  • Borsboom, D. (2006). When does measurement invariance matter? Medical Care, 44, S176–S181. https://doi.org/10.1097/01.mlr.0000245143.08679.cc
  • Brown, T. A. (2015). Confirmatory factor analysis for applied research. Guilford publications.
  • Browne, M. W., & Cudeck, R. (1993). Alternative ways of assessing model fit. Sage Focus Editions, 154, 136–136.
  • Chan, W., & Bentler, P. M. (1993). The covariance structure analysis of Ipsative data. Sociological Methods & Research, 22, 214–247. https://doi.org/10.1177/0049124193022002003
  • Chang, Y.-W., Hsu, N.-J., & Tsai, R.-C. (2017). Unifying differential item functioning in factor analysis for categorical data under a discretization of a normal variant. Psychometrika, 82, 382–406. https://doi.org/10.1007/s11336-017-9562-0
  • Chen, F. F. (2007). Sensitivity of goodness of fit indexes to lack of measurement invariance. Structural Equation Modeling, 14, 464–504. https://doi.org/10.1080/10705510701301834
  • Cheung, G. W., & Rensvold, R. B. (2000). Assessing extreme and acquiescence response sets in cross-cultural research using structural equations modeling. Journal of Cross-Cultural Psychology, 31, 187–212. https://doi.org/10.1177/0022022100031002003
  • Cheung, G. W., & Rensvold, R. B. (2002). Evaluating goodness-of-fit indexes for testing measurement invariance. Structural Equation Modeling, 9, 233–255. https://doi.org/10.1207/S15328007SEM0902_5
  • Chyung, S. Y., Barkin, J. R., & Shamsy, J. A. (2018). Evidence-based survey design: The use of negatively worded items in surveys. Performance Improvement, 57, 16–25. https://doi.org/10.1002/pfi.21749
  • Danner, D., Aichholzer, J., & Rammstedt, B. (2015). Acquiescence in personality questionnaires: Relevance, domain specificity, and stability. Journal of Research in Personality, 57, 119–130. https://doi.org/10.1016/j.jrp.2015.05.004
  • De Jonckere, J., & Rosseel, Y. (2022). Using bounded estimation to avoid nonconvergence in small sample structural equation modeling. Structural Equation Modeling, 29, 412–427. https://doi.org/10.1080/10705511.2021.1982716
  • de la Fuente, J., & Abad, F. J. (2020). Comparing methods for modeling acquiescence in multidimensional partially balanced scales. Psicothema, 32, 590–597. https://doi.org/10.7334/psicothema2020.96
  • D'Urso, E. D., De Roover, K., Vermunt, J. K., & Tijmstra, J. (2022). Scale length does matter: recommendations for measurement invariance testing with categorical factor analysis and item response theory approaches. Behavior Research Methods, 54, 2114–2145. https://doi.org/10.3758/s13428-021-01690-7
  • D'Urso, E. D., Tijmstra, J., Vermunt, J. K., & De Roover, K. (2023). Awareness is bliss: How acquiescence affects exploratory factor analysis. Educational and Psychological Measurement, 83, 433–472. https://doi.org/10.1177/00131644221089857
  • Fabrigar, L. R., Wegener, D. T., MacCallum, R. C., & Strahan, E. J. (1999). Evaluating the use of exploratory factor analysis in psychological research. Psychological Methods, 4, 272–299. https://doi.org/10.1037/1082-989X.4.3.272
  • Ferrando, P. J., Condon, L., & Chico, E. (2004). The convergent validity of acquiescence: An empirical study relating balanced scales and separate acquiescence scales. Personality and Individual Differences, 37, 1331–1340. https://doi.org/10.1016/j.paid.2004.01.003
  • Ferrando, P. J., & Lorenzo-Seva, U. (2010). Acquiescence as a source of bias and model and person misfit: A theoretical and empirical analysis. The British Journal of Mathematical and Statistical Psychology, 63, 427–448. https://doi.org/10.1348/000711009X470740
  • Ferrando, P. J., Morales-Vives, F., & Lorenzo-Seva, U. (2016). Assessing and controlling acquiescent responding when acquiescence and content are related: A comprehensive factor-analytic approach. Structural Equation Modeling, 23, 713–725. https://doi.org/10.1080/10705511.2016.1185723
  • Finch, W. H., & French, B. F. (2018). A simulation investigation of the performance of invariance assessment using equivalence testing procedures. Structural Equation Modeling, 25, 673–686. https://doi.org/10.1080/10705511.2018.1431781
  • French, B. F., & Finch, W. H. (2006). Confirmatory factor analytic procedures for the determination of measurement invariance. Structural Equation Modeling, 13, 378–402. https://doi.org/10.1207/s15328007sem1303_3
  • French, B. F., & Finch, W. H. (2008). Multigroup confirmatory factor analysis: Locating the invariant referent sets. Structural Equation Modeling, 15, 96–113. https://doi.org/10.1080/10705510701758349
  • Guenole, N., & Brown, A. (2014). The consequences of ignoring measurement invariance for path coefficients in structural equation models. Frontiers in Psychology, 5, 980. https://doi.org/10.3389/fpsyg.2014.00980
  • Jeong, S., & Lee, Y. (2019). Consequences of not conducting measurement invariance tests in cross-cultural studies: A review of current research practices and recommendations. Advances in Developing Human Resources, 21, 466–483. https://doi.org/10.1177/1523422319870726
  • Johnson, T., Kulesa, P., Cho, Y. I., & Shavitt, S. (2005). The relation between culture and response styles: Evidence from 19 countries. Journal of Cross-Cultural Psychology, 36, 264–277. https://doi.org/10.1177/0022022104272905
  • Jones, R. N., & Gallo, J. J. (2002). Education and sex differences in the mini-mental state examination: effects of differential item functioning. The Journals of Gerontology. Series B, Psychological Sciences and Social Sciences, 57, P548–P558. https://doi.org/10.1093/geronb/57.6.p548
  • Jöreskog, K. (1970). Simultaneous factor analysis in several populations. ETS Research Bulletin Series, 1970, i–31. https://doi.org/10.1002/j.2333-8504.1970.tb00790.x
  • Jorgensen, T. D., Pornprasertmanit, S., Schoemann, A. M., & Rosseel, Y. (2022). semTools: Useful tools for structural equation modeling. R package version 0.5-6. Retrieved from https://CRAN.R-project.org/package=semTools
  • Liu, M., Harbaugh, A. G., Harring, J. R., & Hancock, G. R. (2017). The effect of extreme response and non-extreme response styles on testing measurement invariance. Frontiers in Psychology, 8, 726. https://doi.org/10.3389/fpsyg.2017.00726
  • MacCallum, R. C., Widaman, K. F., Zhang, S., & Hong, S. (1999). Sample size in factor analysis. Psychological Methods, 4, 84–99. https://doi.org/10.1037/1082-989X.4.1.84
  • Marcoulides, K. M., & Yuan, K.-H. (2017). New ways to evaluate goodness of fit: A note on using equivalence testing to assess structural equation models. Structural Equation Modeling, 24, 148–153. https://doi.org/10.1080/10705511.2016.1225260
  • Marin, G., Gamba, R. J., & Marin, B. V. (1992). Extreme response style and acquiescence among hispanics: The role of acculturation and education. Journal of Cross-Cultural Psychology, 23, 498–509. https://doi.org/10.1177/0022022192234006
  • McNeish, D., & Wolf, M. G. (2023). Dynamic fit index cutoffs for confirmatory factor analysis models. Psychological Methods, 28, 61–88. https://doi.org/10.1037/met0000425
  • Meisenberg, G., & Williams, A. (2008). Are acquiescent and extreme response styles related to low intelligence and education? Personality and Individual Differences, 44, 1539–1550. https://doi.org/10.1016/j.paid.2008.01.010
  • Meredith, W., & Teresi, J. A. (2006). An essay on measurement and factorial invariance. Medical Care, 44, S69–S77. https://doi.org/10.1097/01.mlr.0000245438.73837.89
  • Muthén, B., & Muthén, B. O. (2009). Statistical analysis with latent variables (vol. 123). Wiley.
  • Paulhus, D. L. (1991). Measurement and control of response bias. In J. P. Robinson, P. R. Shaver, & L. S. Wrightsman (Eds.), Measures of personality and social psychological attitudes (pp. 17–59). Academic Press.
  • Putnick, D. L., & Bornstein, M. H. (2016). Measurement invariance conventions and reporting: The state of the art and future directions for psychological research. Developmental Review, 41, 71–90. https://doi.org/10.1016/j.dr.2016.06.004
  • R Core Team. (2013). R: A language and environment for statistical computing [Computer software manual]. Vienna, Austria. Retrieved from http://www.R-project.org/
  • Rios, J. A. (2021). Is differential non-effortful responding associated with type I error in measurement invariance testing? Educational and Psychological Measurement, 81, 957–979. https://doi.org/10.1177/0013164421990429
  • Rosseel, Y. (2012). Lavaan: An R package for structural equation modeling. Journal of Statistical Software, 48, 1–36. https://doi.org/10.18637/jss.v048.i02
  • Rutkowski, L., & Svetina, D. (2017). Measurement invariance in international surveys: Categorical indicators and fit measure performance. Applied Measurement in Education, 30, 39–51. https://doi.org/10.1080/08957347.2016.1243540
  • Savalei, V., & Falk, C. F. (2014). Recovering substantive factor loadings in the presence of acquiescence bias: A comparison of three approaches. Multivariate Behavioral Research, 49, 407–424. https://doi.org/10.1080/00273171.2014.931800
  • Svetina, D., Rutkowski, L., & Rutkowski, D. (2020). Multiple-group invariance with categorical outcomes using updated guidelines: An illustration using M plus and the Lavaan/SEMtools packages. Structural Equation Modeling, 27, 111–130. https://doi.org/10.1080/10705511.2019.1602776
  • Van Vaerenbergh, Y., & Thomas, T. D. (2013). Response styles in survey research: A literature review of antecedents, consequences, and remedies. International Journal of Public Opinion Research, 25, 195–217. https://doi.org/10.1093/ijpor/eds021
  • Weijters, B., Geuens, M., & Schillewaert, N. (2010). The stability of individual response styles. Psychological Methods, 15, 96–110. https://doi.org/10.1037/a0018721
  • Welkenhuysen-Gybels, J., Billiet, J., & Cambré, B. (2003). Adjustment for acquiescence in the assessment of the construct equivalence of Likert-type score items. Journal of Cross-Cultural Psychology, 34, 702–722. https://doi.org/10.1177/0022022103257070
  • Wu, H., & Estabrook, R. (2016). Identification of confirmatory factor analysis models of different levels of invariance for ordered categorical outcomes. Psychometrika, 81, 1014–1045. https://doi.org/10.1007/s11336-016-9506-0
  • Yuan, K.-H., Chan, W., Marcoulides, G. A., & Bentler, P. M. (2016). Assessing structural equation models by equivalence testing with adjusted fit indexes. Structural Equation Modeling, 23, 319–330. https://doi.org/10.1080/10705511.2015.1065414