141
Views
5
CrossRef citations to date
0
Altmetric
Statistical Developments and Applications

Analyzing and Comparing Univariate, Multivariate, and Bifactor Generalizability Theory Designs for Hierarchically Structured Personality Traits

ORCID Icon, ORCID Icon, &
Pages 285-300 | Received 01 May 2023, Accepted 25 Sep 2023, Published online: 08 Nov 2023

References

  • American Educational Research Association (AERA), American Psychological Association (APA), & National Council on Measurement in Education (NCME) (2014). Standards for educational and psychological testing. American Educational Research Association.
  • American Psychological Association (APA) (1954). Technical recommendations for psychological tests and diagnostic techniques. Psychological Bulletin, 51(2, Pt.2), 1–38. https://doi.org/10.1037/h0053479
  • Ark, T. K. (2015). Ordinal generalizability theory using an underlying latent variable framework [Doctoral dissertation]. University of British Columbia.
  • Brennan, R. L. (2001). Generalizability theory. Springer-Verlag.
  • Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika, 16(3), 297–334. https://doi.org/10.1007/BF02310555
  • Cronbach, L. J., Gleser, G. C., Nanda, H., & Rajaratnam, N. (1972). The dependability of behavioral measurements: Theory of generalizability for scores and profiles. Wiley.
  • Cronbach, L. J., Rajaratnam, N., & Gleser, G. C. (1963). Theory of generalizability: A liberalization of reliability theory. British Journal of Statistical Psychology, 16(2), 137–163. https://doi.org/10.1111/j.2044-8317.1963.tb00206.x
  • Cronbach, L. J., Schönemann, P., & McKie, D. (1965). Alpha coefficients for stratified-parallel tests. Educational and Psychological Measurement, 25(2), 291–312. https://doi.org/10.1177/001316446502500201
  • DeYoung, C. G., Quilty, L. C., & Peterson, J. B. (2007). Between facets and domains: 10 aspects of the Big Five. Journal of Personality and Social Psychology, 93(5), 880–896. https://doi.org/10.1037/0022-3514.93.5.880
  • Feinberg, R. A., & Wainer, H. (2014). A simple equation to predict a subscore’s value. Educational Measurement: Issues and Practice, 33(3), 55–56. https://doi.org/10.1111/emip.12035
  • Geiser, C., & Lockhart, G. (2012). A comparison of four approaches to account for method effects in latent state-trait analyses. Psychological Methods, 17(2), 255–283. https://doi.org/10.1037/a0026977
  • Haberman, S. J. (2008). When can subscores have value? Journal of Educational and Behavioral Statistics, 33(2), 204–229. https://doi.org/10.3102/1076998607302636
  • John, O. P., Donahue, E. M., & Kentle, R. L. (1991). The Big Five Inventory—versions 4a and 54. University of California, Berkeley, Institute of Personality and Social Research.
  • Jorgensen, T. D. (2021). How to estimate absolute-error components in structural equation models of generalizability theory. Psych, 3(2), 113–133. https://doi.org/10.3390/psych3020011
  • Jorgensen, T. D., Pornprasertmanit, S., Schoemann, A. M., Rosseel, Y. (2022). semTools: Useful tools for structural equation modeling. R package version 0.5-6. https://CRAN.R-project.org/package=semTools
  • Kumar, S. S., Merkin, A. G., Numbers, K., Sachdev, P. S., Brodaty, H., Kochan, N. A., Trollor, J. N., Mahon, S., & Medvedev, O. (2022). A novel approach to investigate depression symptoms in the aging population using generalizability theory. Psychological Assessment, 34(7), 684–696. https://doi.org/10.1037/pas0001129
  • Le, H., Schmidt, F. L., & Putka, D. J. (2009). The multifaceted nature of measurement artifacts and its implications for estimating construct-level relationships. Organizational Research Methods, 12(1), 165–200. https://doi.org/10.1177/1094428107302900
  • Lord, F. M. (1956). Sampling error due to choice of split in split-half reliability coefficients. The Journal of Experimental Education, 24(3), 245–249. https://doi.org/10.1080/00220973.1956.11010545
  • Lyndon, M. P., Medvedev, O. N., Chen, Y., & Henning, M. A. (2020). Investigating stable and dynamic aspects of student motivation using generalizability theory. Australian Journal of Psychology, 72(2), 199–210. https://doi.org/10.1111/ajpy.12276
  • McCrae, R. R., & Costa, P. T. (2010). NEO Inventories professional manual. Psychological Assessment Resources.
  • Medvedev, O. N., Krägeloh, C. U., Narayanan, A., & Siegert, R. J. (2017). Measuring mindfulness: Applying generalizability theory to distinguish between state and trait. Mindfulness, 8(4), 1036–1046. https://doi.org/10.1007/s12671-017-0679-0
  • Miller, Y. R., Medvedev, O. N., Hwang, Y.-S., & Singh, N. N. (2021). Applying generalizability theory to the Perceived Stress Scale to evaluate stable and dynamic aspects of educators’ stress. International Journal of Stress Management, 28(2), 147–153. https://doi.org/10.1037/str0000207
  • Paterson, J., Medvedev, O. N., Sumich, A., Tautolo, E.-S., Krägeloh, C. U., Sisk, R., McNamara, R. K., Berk, M., Narayanan, A., & Siegert, R. J. (2018). Distinguishing transient versus stable aspects of depression in New Zealand Pacific Island children using generalizability theory. Journal of Affective Disorders, 227, 698–704. https://doi.org/10.1016/j.jad.2017.11.075
  • Rajaratnam, N., Cronbach, L. J., & Gleser, G. C. (1965). Generalizability of stratified-parallel tests. Psychometrika, 30(1), 39–56. https://doi.org/10.1007/BF02289746
  • Reise, S. P., Bonifay, W. E., & Haviland, M. G. (2013). Scoring and modeling psychological measures in the presence of multidimensionality. Journal of Personality Assessment, 95(2), 129–140. https://doi.org/10.1080/00223891.2012.725437
  • Rodriguez, A., Reise, S. P., & Haviland, M. G. (2016a). Applying bifactor statistical indices in the evaluation of psychological measures. Journal of Personality Assessment, 98(3), 223–237. https://doi.org/10.1080/00223891.2015.1089249
  • Rodriguez, A., Reise, S. P., & Haviland, M. G. (2016b). Evaluating bifactor models: Calculating and interpreting statistical indices. Psychological Methods, 21(2), 137–150. https://doi.org/10.1037/met0000045
  • Rosseel, Y. (2012). lavaan: An R package for structural equation modeling. Journal of Statistical Software, 48(2), 1–36. https://doi.org/10.18637/jss.v048.i02
  • Saucier, G. (1994). Mini-markers: A brief version of Goldberg’s unipolar Big-Five markers. Journal of Personality Assessment, 63(3), 506–516. https://doi.org/10.1207/s15327752jpa6303_8
  • Schmidt, F. L., Le, H., & Ilies, R. (2003). Beyond alpha: An empirical investigation of the effects of different sources of measurement error on reliability estimates for measures of individual differences constructs. Psychological Methods, 8(2), 206–224. https://doi.org/10.1037/1082-989X.8.2.206
  • Soto, C. J., & John, O. P. (2017). The next Big Five Inventory (BFI-2): Developing and assessing a hierarchical model with 15 facets to enhance bandwidth, fidelity, and predictive power. Journal of Personality and Social Psychology, 113(1), 117–143. https://doi.org/10.1037/pspp0000096
  • Steyer, R., Ferring, D., & Schmitt, M. J. (1992). States and traits in psychological assessment. European Journal of Psychological Assessment, 8(2), 79–98. https://doi.org/10.1027/1015-5759/a000413
  • Thorndike, R. L. (1951). Reliability. In E. F. Lindquist (Ed.), Educational measurement (pp. 560–620). American Council on Education.
  • Tryon, R. C. (1957). Reliability and behavior domain validity: Reformulation and historical critique. Psychological Bulletin, 54(3), 229–249. https://doi.org/10.1037/h0047980
  • van Bork, R., Rhemtulla, M., Sijtsma, K., & Borsboom, D. (2022). A causal theory of error scores. Psychological Methods, 1–20. Advance online publication. https://doi.org/10.1037/met0000521
  • Vispoel, W. P., Hong, H., & Lee, H. (2023). Benefits of doing generalizability theory analyses within structural equation modeling frameworks: Illustrations using the Rosenberg Self-Esteem Scale [Teacher’s corner]. Structural Equation Modeling: A Multidisciplinary Journal, 1–17. Advance online publication. https://doi.org/10.1080/10705511.2023.2187734
  • Vispoel, W. P., Hong, H., Lee, H., & Jorgensen, T. R. (in press). Analyzing complete generalizability theory designs using structural equation models. Applied Measurement in Education,
  • Vispoel, W. P., & Lee, H. (2023). Merging generalizability theory and bifactor modeling to improve psychological assessments. Psychology and Psychotherapy: Review Study, 7, 1–4. https://crimsonpublishers.com/pprs/pdf/PPRS.000652.pdf
  • Vispoel, W. P., Lee, H., Chen, T., & Hong, H. (2023a). Using structural equation modeling techniques to reproduce and extend ANOVA-based generalizability theory analyses for psychological assessments. Psych, 5(2), 249–273. https://doi.org/10.3390/psych5020019
  • Vispoel, W. P., Lee, H., Chen, T., & Hong, H. (2023b). Extending applications of generalizability theory-based bifactor model designs. Psych, 5(2), 545–575. https://doi.org/10.3390/psych5020036
  • Vispoel, W. P., Lee, H., Hong, H., & Chen, T. (2023). Applying multivariate generalizability theory to psychological assessments. Psychological Methods, 1–23. Advance online publication. https://doi.org/10.1037/met0000606
  • Vispoel, W. P., Lee, H., & Hong, H. (2023). Analyzing multivariate generalizability theory designs within structural equation modeling frameworks [Teacher’s corner]. Structural Equation Modeling: A Multidisciplinary Journal, 1–19. Advance online publication. https://doi.org/10.1080/10705511.2023.2222913
  • Vispoel, W. P., Lee, H., Xu, G., & Hong, H. (2022). Expanding bifactor models of psychological traits to account for multiple sources of measurement error. Psychological Assessment, 34(12), 1093–1111. https://doi.org/10.1037/pas0001170
  • Vispoel, W. P., Lee, H., Xu, G., & Hong, H. (2023). Integrating bifactor models into a generalizability theory based structural equation modeling framework. The Journal of Experimental Education, 91(4), 718–738. https://doi.org/10.1080/00220973.2022.2092833
  • Vispoel, W. P., Morris, C. A., & Kilinc, M. (2018a). Applications of generalizability theory and their relations to classical test theory and structural equation modeling. Psychological Methods, 23(1), 1–26. https://doi.org/10.1037/met0000107
  • Vispoel, W. P., Morris, C. A., & Kilinc, M. (2018b). Practical applications of generalizability theory for designing, evaluating, and improving psychological assessments. Journal of Personality Assessment, 100(1), 53–67. https://doi.org/10.1080/00223891.2017.1296455
  • Vispoel, W. P., Morris, C. A., & Kilinc, M. (2018c). Using G-theory to enhance evidence of reliability and validity for common uses of the Paulhus Deception Scales. Assessment, 25(1), 69–83. https://doi.org/10.1177/1073191116641182
  • Vispoel, W. P., Morris, C. A., & Kilinc, M. (2018d). Using generalizability theory to disattenuate correlation coefficients for multiple sources of measurement error. Multivariate Behavioral Research, 53(4), 481–501. https://doi.org/10.1080/00273171.2018.1457938
  • Vispoel, W. P., Morris, C. A., & Kilinc, M. (2019). Using generalizability theory with continuous latent response variables. Psychological Methods, 24(2), 153–178. https://doi.org/10.1037/met0000177
  • Vispoel, W. P., & Tao, S. (2013). A generalizability analysis of score consistency for the Balanced Inventory of Desirable Responding. Psychological Assessment, 25(1), 94–104. https://doi.org/10.1037/a0029061
  • Vispoel, W. P., Xu, G., & Kilinc, M. (2021). Expanding G-theory models to incorporate congeneric relationships: Illustrations using the Big Five Inventory. Journal of Personality Assessment, 103(4), 429–442. https://doi.org/10.1080/00223891.2020.1808474
  • Vispoel, W. P., Xu, G., & Schneider, W. S. (2022a). Interrelationships between latent state-trait theory and generalizability theory in a structural equation modeling framework. Psychological Methods, 27(5), 773–803. https://doi.org/10.1037/met0000290
  • Vispoel, W. P., Xu, G., & Schneider, W. S. (2022b). Using parallel splits with self-report and other measures to enhance precision in generalizability theory analyses. Journal of Personality Assessment, 104(3), 303–319. https://doi.org/10.1080/00223891.2021.1938589
  • Wan, C., Chen, Y., Gao, L., Zhang, Q., Quan, P., & Sun, X. (2020). Development and validation of the peptic ulcer scale under the system of quality of life instruments for chronic diseases based on classical test theory and generalizability theory. BMC Gastroenterology, 20(1), 422. https://doi.org/10.1186/s12876-020-01562-y

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.