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Articles

Examining Trait × Method Interactions Using Mixture Distribution Multitrait–Multimethod Models

REFERENCES

  • American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.). Arlington, VA: American Psychiatric Publishing.
  • Bagozzi, R. P., & Yi, Y. (1992). Testing hypotheses about methods, traits, and communalities in the direct-product model. Applied Psychological Measurement, 16, 373–380. doi:10.1177/014662169201600409
  • Bauer, D. J., & Curran, P. J. (2003). Distributional assumptions of growth mixture models: Implications for overextraction of latent trajectory classes. Psychological Methods, 8, 338–363. doi:10.1037/1082-989X.8.3.338
  • Boomsma, A. (1985). Nonconvergence, improper solutions, and starting values in LISREL maximum likelihood estimation. Psychometrika, 50, 229–242. doi:10.1007/BF02294248
  • Browne, M. (1984). The decomposition of multitrait–multimethod matrices. British Journal of Mathematical & Statistical Psychology, 37(1), 1–21. doi:10.1111/bmsp.1984.37.issue-1
  • Burns, G. L., & Lee, S. (2011). Child and Adolescent Disruptive Behavior Inventory–Parent version 5.0. Pullman, WA: Author.
  • Burns, G. L., Servera, M., Bernard, M. D. M., Carrillo, J. M., & Geiser, C. (2014). Ratings of ADHD symptoms and academic impairment by mothers, fathers, teachers, and aides: Construct validity within and across settings as well as occasions. Psychological Assessment, 26, 1247–1258. doi:10.1037/pas0000008
  • Byrne, B. M., Shavelson, R. J., & Muthén, B. (1989). Testing for the equivalence of factor covariance and mean structures: The issue of partial measurement invariance. Psychological Bulletin, 105, 456–466. doi:10.1037/0033-2909.105.3.456
  • Campbell, D. T., & Fiske, D. W. (1959). Convergent and discriminant validation by the multitrait–multimethod matrix. Psychological Bulletin, 56, 81–105. doi:10.1037/h0046016
  • Chen, F., Bollen, K. A., Paxton, P., Curran, P. J., & Kirby, J. B. (2001). Improper solutions in structural equation models: Causes, consequences, and strategies. Sociological Methods & Research, 29, 468–508. doi:10.1177/0049124101029004003
  • Cole, D. A., & Maxwell, S. E. (1985). Multitrait–multimethod comparisons across populations: A confirmatory factor analytic approach. Multivariate Behavioral Research, 20, 389–417. doi:10.1207/s15327906mbr2004_3
  • Cole, D. A., Truglio, R., & Peeke, L. (1997). Relation between symptoms of anxiety and depression in children: A multitrait–multimethod–multigroup assessment. Journal of Consulting and Clinical Psychology, 65(1), 110–119. doi:10.1037/0022-006X.65.1.110
  • Collins, L. M., & Lanza, S. T. (2010). Latent class and latent transition analysis with applications in the social, behavioral, and health sciences. New York, NY: Wiley.
  • Courvoisier, D. S., Eid, M., & Nussbeck, F. W. (2007). Mixture distribution latent state–trait analysis: Basic ideas and applications. Psychological Methods, 12(1), 80–104. doi:10.1037/1082-989X.12.1.80
  • Eid, M. (2000). A multitrait–multimethod model with minimal assumptions. Psychometrika, 65, 241–261. doi:10.1007/BF02294377
  • Eid, M. (2006). Methodological approaches for analyzing multimethod data. In M. Eid, & E. Diener (Eds.), Handbook of multimethod measurement in psychology (pp. 223–230). Washington, DC: American Psychological Association.
  • Eid, M., Lischetzke, T., & Nussbeck, F. W. (2006). Structural equation models for multitrait–multimethod data. In M. Eid & E. Diener (Eds.), Handbook of multimethod measurement in psychology (pp. 283–299). Washington, DC: American Psychological Association.
  • Eid, M., Lischetzke, T., Nussbeck, F. W., & Trierweiler, L. I. (2003). Separating trait effects from trait-specific method effects in multitrait–multimethod models: A multiple-indicator CT–C (M–1) model. Psychological Methods, 8(1), 38–60. doi:10.1037/1082-989X.8.1.38
  • Fiske, D. W. (1982). Convergent-discriminant validation in measurements and research strategies. New Directions for Methodology of Social & Behavioral Science, 12, 77–92.
  • Fiske, D. W., & Campbell, D. T. (1992). Citations do not solve problems. Psychological Bulletin, 112, 393–395. doi:10.1037/0033-2909.112.3.393
  • Geiser, C., Burns, G. L., & Servera, M. (2014). Testing for measurement invariance and latent mean differences across methods: Interesting incremental information from multitrait–multimethod studies. Frontiers in Psychology, 5, 1–19. doi:10.3389/fpsyg.2014.01216
  • Geiser, C., Eid, M., West, S. G., Lischetzke, T., & Nussbeck, F. W. (2012). A comparison of method effects in two confirmatory factor models for structurally different methods. Structural Equation Modeling, 19, 409–436. doi:10.1080/10705511.2012.687658
  • Kenny, D. A., & Kashy, D. A. (1992). Analysis of the multitrait–multimethod matrix by confirmatory factor analysis. Psychological Bulletin, 112(1), 165–172. doi:10.1037/0033-2909.112.1.165
  • Lazarsfeld, P. F., & Henry, N. W. (1968). Latent structure analysis. Boston, MA: Houghton Mifflin.
  • Little, T. D., Rhemtulla, M., Kl., G., & Schoemann, A. M. (2013). Why the item versus parcels controversy needn’t be one. Psychological Methods, 18, 285–300. doi:10.1037/a0033266
  • Lubke, G. H., & Muthén, B. (2005). Investigating population heterogeneity with factor mixture models. Psychological Methods, 10(1), 21–39. doi:10.1037/1082-989X.10.1.21
  • Lubke, G. H., & Muthén, B. (2007). Performance of factor mixture models as a function of model size, covariate effects, and class-specific parameters. Structural Equation Modeling, 14, 26–47. doi:10.1080/10705510709336735
  • Marsh, H. W., & Hocevar, D. (1988). A new, more powerful approach to multitrait–multimethod analyses: Application of second-order confirmatory factor analysis. Journal of Applied Psychology, 73, 107–117. doi:10.1037/0021-9010.73.1.107
  • Marsh, H. W., Lüdtke, O., Nagengast, B., Morin, A. J. S., & Von Davier, M. (2013). Why item parcels are (almost) never appropriate: Two wrongs do not make a right—Camouflaging misspecifications with item parcels in CFA models. Psychological Methods, 18, 257–284. doi:10.1037/a0032773
  • McCutcheon, A. L. (1987). Latent class analysis. Thousand Oaks, CA: Sage.
  • McLachlan, G. J., & Peel, D. (2000). Finite mixture models. New York, NY: Wiley.
  • Muthén, B. O. (2001a). Latent variable mixture modeling. In G. A. Marcoulides & R. E. Schumacker (Eds.), New developments and techniques in structural equation modeling (pp. 1–33). Mahwah, NJ: Erlbaum.
  • Muthén, B. O. (2001b). Second-generation structural equation modeling with a combination of categorical and continuous latent variables: New opportunities for latent class–latent growth modeling. In L. M. Collins & A. G. Sayer (Eds.), New methods for the analysis of change (pp. 291–322). Washington, DC: American Psychological Association. doi:10.1037/10409-010
  • Muthén, B., & Muthén, L. K. (2000). Integrating person-centered and variable-centered analyses: Growth mixture modeling with latent trajectory classes. Alcoholism: Clinical and Experimental Research, 24, 882–891. doi:10.1111/j.1530-0277.2000.tb02070.x
  • Muthén, L. K., & Muthén, B. O. (1998–2012). Mplus user’s guide (7th ed.). Los Angeles, CA: Muthén & Muthén.
  • Nylund, K. L., Asparouhov, T., & Muthén, B. O. (2007). Deciding on the number of classes in latent class analysis and growth mixture modeling: A Monte Carlo simulation study. Structural Equation Modeling, 14, 535–569. doi:10.1080/10705510701575396
  • Oberski, D. L., Hagenaars, J. A. P., & Saris, W. E. (2015). The latent class multitrait–multimethod model. Psychological Methods, 20, 422–443. doi:10.1037/a0039783
  • Podsakoff, P. M., MacKenzie, S. B., & Podsakoff, N. P. (2012). Sources of method bias in social science research and recommendations on how to control it. Annual Review of Psychology, 63, 539–569. doi:10.1146/annurev-psych-120710-100452
  • Pohl, S., & Steyer, R. (2010). Modeling common traits and method effects in multitrait–multimethod analysis. Multivariate Behavioral Research, 45, 45–72. doi:10.1080/00273170903504729
  • Pohl, S., Steyer, R., & Kraus, K. (2008). Modelling method effects as individual causal effects. Journal of the Royal Statistical Society: Series A (Statistics in Society), 171(1), 41–63.
  • Raykov, T., Marcoulides, G. A., & Li, T. (2015). Evaluation of measurement instrument criterion validity in finite mixture settings. Educational and Psychological Measurement. Advance online publication. doi: 10.1177/0013164415613542.
  • Schoot, R. V. D., Lugtig, P., & Hox, J. (2012). A checklist for testing measurement invariance. European Journal of Developmental Psychology, 9, 486–492. doi:10.1080/17405629.2012.686740
  • van Driel, O. P. (1978). On various causes of improper solutions in maximum likelihood factor analysis. Psychometrika, 43, 225–243. doi:10.1007/BF02293865
  • Vermunt, J. K., & Magidson, J. (2002). Latent class cluster analysis. In J. A. Hagenaars & A. L. McCutcheon (Eds.), Applied latent class analysis (pp. 89–106). Cambridge, UK: Cambridge University Press.
  • Visser, S. N., Danielson, M. L., Bitsko, R. H., Holbrook, J. R., Kogan, M. D., Ghandour, R. M., … Blumberg, S. J. (2014). Trends in the parent-report of health care provider-diagnosed and medicated attention-deficit/hyperactivity disorder: United States, 2003–2011. Journal of the American Academy of Child and Adolescent Psychiatry, 53, 34–46. doi:10.1016/j.jaac.2013.09.001
  • Widaman, K. F. (1985). Hierarchically nested covariance structure models for multitrait–multimethod data. Applied Psychological Measurement, 9(1), 1–26. doi:10.1177/014662168500900101
  • Widaman, K. F., & Reise, S. P. (1997). Exploring the measurement invariance of psychological instruments: Applications in the substance use domain. In K. J. Bryant, M. E. Windle, & S. G. West (Eds.), The science of prevention: Methodological advances from alcohol and substance abuse research (pp. 281–384). American Psychological Association.
  • Wothke, W., & Browne, M. W. (1990). The direct product model for the MTMM matrix parameterized as a second order factor analysis model. Psychometrika, 55, 255–262. doi:10.1007/BF02295286

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