Multilevel sem strategies for evaluating mediation in three-level data

Multivariate Behavioral Research

Volumn 46, Issue 4, 2011, Pages 691-731

  Preacher, Kristopher J ^a  

^a UNIVERSITY OF KANSAS   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 79961219427     PISSN: 00273171     EISSN: None     Source Type: Journal    
DOI: 10.1080/00273171.2011.589280     Document Type: Article

References (74)

1. Ansari, A., Jedidi, K., & Jagpal, S. (2000). A hierarchical Bayesian methodology for treating heterogeneity in structural equation models. Marketing Science, 19, 328-347.
2. Bauer, D. J. (2003). Estimating multilevel linear models as structural equation models. Journal of Educational and Behavioral Statistics, 28, 135-167.
3. Bauer, D. J., Preacher, K. J., & Gil, K. M. (2006). Conceptualizing and testing random indirect effects and moderated mediation in multilevel models: New procedures and recommendations. Psychological Methods, 11, 142-163.
4. Bentler, P. M., & Liang, J. (2003). Two-level mean and covariance structures: Maximum likelihood via an EM algorithm. In S. P. Reise & N. Duan (Eds.), Multilevel modeling: Methodological advances, issues, and applications (pp. 53-70). Mahwah, NJ: Erlbaum.
5. Boker, S. M., Neale, M. C., Maes, H. H., Wilde, M. J., Spiegel, M., Brick, T. R., Fox, J. (2010). OpenMx reference manual (Version 1.0.0-1448). Charlottesville, VA: University of Virginia.
6. Bollen, K. A., Bauer, D. J., Christ, S. L., & Edwards, M. C. (2010). An overview of structural equation models and recent extensions. In S. Kolenikov, D. Steinley, & L. Thombs (Eds.), Recent developments in social science statistics (pp. 37-80). New York, NY: Wiley.
7. Bollen, K. A., & Curran, P. J. (2006). Latent curve models: A structural equation perspective. New York, NY: Wiley.
8. Bovaird, J. A. (2007). Multilevel structural equation models for contextual factors. In T. D. Little, J. A. Bovaird, & N. A. Card (Eds.), Modeling contextual effects in longitudinal studies (pp. 149-182). Mahwah, NJ: Erlbaum.
9. Chou, C. P., Bentler, P. M., & Pentz, M. A. (2000). A two-stage approach to multilevel structural equation models: Application to longitudinal data. In T. D. Little, K. U. Schnabel, & J. Baumert (Eds.), Modeling longitudinal and multilevel data: Practical issues, applied approaches and specific examples (pp. 33-49). Mahwah, NJ: Erlbaum.
10. Curran, P. J. (2003). Have multilevel models been structural equation models all along? Multivariate Behavioral Research, 38, 529-569.
11. Duncan, T. E., Duncan, S. C., Alpert, A., Hops, H., Stoolmiller, M., & Muthén, B. (1997). Latent variable modeling of longitudinal and multilevel substance use data. Multivariate Behavioral Research, 32, 275-318.
12. Duncan, T. E., Duncan, S. C., Okut, H., Strycker, L. A., & Li, F. (2002). An extension of the general latent variable growth modeling framework to four levels of the hierarchy. Structural Equation Modeling, 9, 303-326.
13. Duncan, T. E., Duncan, S. C., & Strycker, L. A. (2006). Latent variable growth curve modeling. Mahwah, NJ: Erlbaum.
14. Goldstein, H., & McDonald, R. P. (1988). A general model for the analysis of multilevel data. Psychometrika, 53, 455-467.
15. Goodman, L. A. (1960). On the exact variance of products. Journal of the American Statistical Association, 55, 708-713.
16. Gottfredson, N. C., Panter, A. T., Daye, C. E., Allen, W. A. & Wightman, L. F. (2009). The effects of educational diversity in a national sample of law students: Fitting multilevel latent variable models in data with categorical indicators. Multivariate Behavioral Research, 44, 305-331.
17. Heck, R. H., & Thomas, S. L. (2009). An introduction to multilevel modeling techniques (2nd ed.). New York, NY: Routledge.
18. Hedeker, D., & Gibbons, R. D. (2006). Longitudinal data analysis. Hoboken, NJ: Wiley.
19. Hox, J. J. (2010). Multilevel analysis: Techniques and applications (2nd ed.). New York, NY: Routledge.
20. Hox, J. J., Maas, C. J. M., & Brinkhuis, M. J. S. (2010). The effect of estimation method and sample size in multilevel structural equation modeling. Statistica Neerlandica, 64, 157-170.
21. Jedidi, K., & Ansari, A. (2001). Bayesian structural equation models for multilevel data. In G. A. Marcoulides& R. E. Schumacker (Eds.), New developments and techniques in structural equation modeling (pp. 129-157). Mahwah, NJ: Erlbaum.
22. Julian, M. W. (2001). The consequences of ignoring multilevel data structures in nonhierarchical covariance modeling. Structural Equation Modeling, 8, 325-352.
23. Kaplan, D. (2009). Structural equation modeling (2nd ed.). Thousand Oaks, CA: Sage.
24. Kenny, D. A., Kashy, D. A., & Bolger, N. (1998). Data analysis in social psychology. In D. Gilbert, S. T. Fiske, & G. Lindzey (Eds.), The handbook of social psychology (4th ed., Vol. 1, pp. 223-265). New York, NY: McGraw-Hill.
25. Kenny, D. A., Korchmaros, J. D., & Bolger, N. (2003). Lower level mediation in multilevel models. Psychological Methods, 8, 115-128.
26. Kreft, I. G. G., de Leeuw, J., & Aiken, L. S. (1995). The effect of different forms of centering in hierarchical linear models. Multivariate Behavioral Research, 30, 1-21.
27. Krull, J. L., & MacKinnon, D. P. (1999). Multilevel mediation modeling in group-based intervention studies. Evaluation Review, 23, 418-444.
28. Krull, J. L., & MacKinnon, D. P. (2001). Multilevel modeling of individual and group level mediated effects. Multivariate Behavioral Research, 36, 249-277.
29. Lee, S.-Y. (1990). Multilevel analysis of structural equation models. Biometrika, 77, 763-772.
30. Lee, S.-Y., & Poon, W.-Y. (1998). Analysis of two-level structural equation models via EM type algorithms. Statistica Sinica, 8, 749-766.
31. Liang, J., & Bentler, P. M. (2004). An EM algorithm for fitting two-level structural equation models. Psychometrika, 69, 101-122.
32. Lüdtke, O., Marsh, H. W., Robitzsch, A., Trautwein, U., Asparouhov, T., & Muthén, B. (2008). The multilevel latent covariate model: A new, more reliable approach to group-level effects in contextual studies. Psychological Methods, 13, 203-229.
33. MacCallum, R. C., Kim, C., Malarkey, W. B., & Kiecolt-Glaser, J. K. (1997). Studying multivariate change using multilevel models and latent curve models. Multivariate Behavioral Research, 32, 215-253.
34. MacKinnon, D. P. (2008). Introduction to statistical mediation analysis. New York, NY: Lawrence Erlbaum Associates.
35. MacKinnon, D. P., Fritz, M. S., Williams, J., & Lockwood, C. M. (2007). Distribution of the product confidence limits for the indirect effect: Program PRODCLIN. Behavior Research Methods, 39, 384-389.
36. MacKinnon, D. P., Lockwood, C. M., & Williams, J. (2004). Confidence limits for the indirect effect: Distribution of the product and resampling methods. Multivariate Behavioral Research, 39, 99-128.
37. McArdle, J. J. (1988). Dynamic but structural equation modeling of repeated measures data. In R. B. Cattell & J. Nesselroade (Eds.), Handbook of multivariate experimental psychology (2nd ed., pp. 561-614). New York, NY: Plenum.
38. McDonald, R. P., & Goldstein, H. I. (1989). Balanced versus unbalanced designs for linear structural relations in two-level data. British Journal of Mathematical and Statistical Psychology, 42, 215-235.
39. Mehta, P. D., & Neale, M. C. (2005). People are variables too: Multilevel structural equation modeling. Psychological Methods, 10, 259-284.
40. Mehta, P. D., & West, S. G. (2000). Putting the individual back into individual growth curves. Psychological Methods, 5, 23-43.
41. Meredith, W., & Tisak, J. (1990). Latent curve analysis. Psychometrika, 55, 107-122.
42. Moerbeek, M. (2004). The consequences of ignoring a level of nesting in multilevel analysis. Multivariate Behavioral Research, 39, 129-149.
43. Muthén, B. O. (1989). Latent variable modeling in heterogeneous populations. Psychometrika, 54, 557-585.
44. Muthén, B. O. (1994). Multilevel covariance structure analysis. SociologicalMethods and Research, 22, 376-398.
45. Muthén, B. (1997a). Latent variable growth modeling with multilevel data. In M. Berkane (Ed.), Latent variable modeling with application to causality (pp. 149-161), New York, NY: Springer-Verlag.
46. Muthén, B. (1997b). Latent variable modeling of longitudinal and multilevel data. In A. Raftery (Ed.), Sociological methodology (pp. 453-480). Boston, MA: Blackwell.
47. Muthén, B. (2010). Bayesian analysis in Mplus: A brief introduction (Tech. Rep., Version 3). Retrieved from http://statmodel.com
48. Muthén, B. O., & Asparouhov, T. (2008). Growth mixture modeling: Analysis with non-Gaussian random effects. In G. Fitzmaurice, M. Davidian, G. Verbeke, & G. Molenberghs (Eds.), Longitudinal data analysis (pp. 143-165). Boca Raton, FL: Chapman & Hall/CCM.
49. Muthén, B. O., & Asparouhov, T. (2011). Beyondmultilevel regressionmodeling:Multilevel analysis in a general latent variable framework. In J. J. Hox & J. K. Roberts (Eds.), Handbook of advanced multilevel analysis (pp. 15-40). New York, NY: Taylor & Francis.
50. Muthén, L. K., & Muthén, B. O. (1998-2010). Mplus user's guide: Statistical analysis with latent variables (6th ed.). Los Angeles, CA: Author.
51. Neale, M. C., Boker, S. M., Xie, G., & Maes, H. H. (2003). Mx: Statistical modeling (6th ed.). Richmond: Virginia Commonwealth University, Department of Psychiatry.
52. Neuhaus, J. M., & Kalbfleisch, J. D. (1998). Between- and within-cluster covariate effects in the analysis of clustered data. Biometrics, 54, 638-645.
53. Neuhaus, J. M., & McCulloch, C. E. (2006). Separating between- and within-cluster covariate effects by using conditional and partitioning methods. Journal of the Royal Statistical Society, B, 68, 859-872.
54. Pituch, K. A., Murphy, D. L., & Tate, R. L. (2010). Three-level models for indirect effects in school- and class-randomized experiments in education. The Journal of Experimental Education, 78, 60-95.
55. Pituch, K. A., & Stapleton, L. M. (2008). The performance of methods to test upper-level mediation in the presence of nonnormal data. Multivariate Behavioral Research, 43, 237-267.
56. Pituch, K. A., Stapleton, L. M., & Kang, J. Y. (2006). A comparison of single sample and bootstrap methods to assess mediation in cluster randomized trials. Multivariate Behavioral Research, 41, 367-400.
57. Pituch, K. A., Whittaker, T. A., & Stapleton, L. M. (2005). A comparison of methods to test for mediation in multisite experiments. Multivariate Behavioral Research, 40, 1-23.
58. Preacher, K. J., Zhang, Z., & Zyphur, M. J. (2011). Alternative methods for assessing mediation in multilevel data: The advantages of multilevel SEM. Structural Equation Modeling, 18, 161-182.
59. Preacher, K. J., Zyphur, M. J., & Zhang, Z. (2010). A general multilevel SEM framework for assessing multilevel mediation. Psychological Methods, 15, 209-233.
60. Rabe-Hesketh, S., Skrondal, A., & Pickles, A. (2004). Generalized multilevel structural equation modeling. Psychometrika, 69, 167-190.
61. Rabe-Hesketh, S., Skrondal, A., & Zheng, X. (2007). Multilevel structural equation modeling. In S.-Y. Lee (Ed.), Handbook of latent variable and related models (pp. 209-227). Amsterdam, The Netherlands: Elsevier.
62. Raudenbush, S. W., & Bryk, A. S. (2002). Hierarchical linear models (2nd ed.). Newbury Park, CA: Sage.
63. Raudenbush, S. W., Rowan, B., & Kang, S. J. (1991). A multilevel, multivariate model of studying school climate with estimation via the EM algorithm and application to U. S. high school data. Journal of Educational Statistics, 16, 296-330.
64. Raykov, T. (2010). Proportion of third-level variation in multi-level studies: A note on an interval estimation procedure. British Journal of Mathematical and Statistical Psychology, 63, 417-426.
65. Roesch, S. C., Aldridge, A. A., Stocking, S. N., Villodas, F., Leung, Q., Bartley, C. E., & Black, L. J. (2010). Multilevel factor analysis and structural equation modeling of daily diary coping data: Modeling trait and state variation. Multivariate Behavioral Research, 45, 767-789.
66. Ryu, E., & West, S. G. (2009). Level-specific evaluation of model fit in multilevel structural equation modeling. Structural Equation Modeling, 16, 583-601.
67. Schmidt, W. H. (1969). Covariance structure analysis of the multivariate random effects model (Unpublished doctoral dissertation). University of Chicago, Chicago, IL.
68. Spiegelhalter, D., Thomas, A., Best, N., & Lunn, D. (2010). OpenBUGS user manual. Retrieved from: http://www.openbugs.info
69. Statistics Canada. (1996). Growing up in Canada: National longitudinal survey of children and youth. Ottawa, Canada: Minister of Industry.
70. U.S. Department of Education, National Center for Education Statistics. (2000). Early childhood longitudinal study, kindergarten class of 1998-99. Washington, DC: Author.
71. Vander Weele, T. J. (2010). Direct and indirect effects for neighborhood-based clustered and longitudinal data. Sociological Methods & Research, 38, 515-544.
72. Yau, L. H.-Y., Lee, S.-Y., & Poon, W.-Y. (1993). Covariance structure analysis with three-level data. Computational Statistics & Data Analysis, 15, 159-178.
73. Yuan, K.-H., & Bentler, P. M. (2007). Multilevel covariance structure analysis by fitting multiple single-level models. Sociological Methodology, 37, 53-82.
74. Zhang, Z., Zyphur, M. J., & Preacher, K. J. (2009). Testing multilevel mediation using hierarchical linear models: Problems and solutions. Organizational Research Methods, 12, 695-719.