Residual structures in latent growth curve modeling

Structural Equation Modeling

Volumn 17, Issue 3, 2010, Pages 424-442

  Grimm, Kevin J ^a   Widaman, Keith F ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMMON SPECIFICATION; LATENT GROWTH CURVES; MODEL CONVERGENCE; MULTILEVEL MODEL; REPEATED MEASURES; RESIDUAL STRUCTURE; RESIDUAL VARIANCE; STRUCTURAL EQUATION MODELING;

REGRESSION ANALYSIS;

SPECIFICATIONS;

EID: 77954446028     PISSN: 10705511     EISSN: None     Source Type: Journal    
DOI: 10.1080/10705511.2010.489006     Document Type: Article

References (30)

1. Blozis, S. A. (2004). Structured latent curve models for the study of change in multivariate repeated measures. Psychological Methods, 9, 334-353.
2. Blozis, S. A. (2007). On fitting non-linear latent curve models to multiple variables measured longitudinally. Structural Equation Modeling, 14, 179-201.
3. Blozis, S. A., Harring, J. R., & Mels, G. (2008). Using LISREL to fit nonlinear latent curve models. Structural Equation Modeling, 15, 346-369.
4. Browne, M. W. (1993). Structured latent curve models. In C. M. Cuadras & C. R. Rao (Eds.), Multivariate analysis: Future directions 2 (pp. 171-198). Amsterdam: North-Holland.
5. Browne, M. W., & du Toit, S. H. C. (1991). Models for learning data. In L. Collins & J. L. Horn (Eds.), Best methods for the analysis of change (pp. 47-68). Washington, DC: APA.
6. Bryk, A. S., & Raudenbush, S. W. (1987). Application of hierarchical linear models to assessing change. Psychological Bulletin, 101, 147-158.
7. Bryk, A. S., & Raudenbush, S. W. (1992). Hierarchical linear models: Applications and data analysis methods. Newbury Park, CA: Sage.
8. Center for Human Resource Research. (2004). A guide to the 1979-2002 National Longitudinal Survey of Youth. Washington, DC: U.S. Department of Labor, Bureau of Labor Statistics.
9. Cudeck, R., & Klebe, K. J. (2002). Multiphase mixed effects models for repeated measures data. Psychological Methods, 7, 41-63.
10. Dunn, L. M., & Dunn, L. M. (1981). Manual for the Peabody Picture Vocabulary Test-revised. Circle Pines, MN: American Guidance Service.
11. Dunn, L. M., & Markwardt, F. C. (1970). Manual for the Peabody Individual Achievement Test. Circle Pines, MN: American Guidance Service.
12. Embretson, S. R., & Reise, S. P. (2000). Item response theory for psychologists. Mahwah, NJ: Lawrence Erlbaum Associates.
13. Ferrer, E., Hamagami, F., & McArdle, J. J. (2004). Modeling latent growth curves with incomplete data using different types of structural equation modeling and multilevel software. Structural Equation Modeling, 11, 452-483.
14. Ferron, J., Dailey, R., & Yi, Q. (2002). Effects of misspecifying the first-level error structure in two-level models of change. Multivariate Behavioral Research, 37, 379-403.
15. Grimm, K. J., & Ram, N. (2009). Nonlinear growth models in Mplus and SAS. Structural Equation Modeling, 16, 676-701.
16. Kwok, O., West, S. G., & Green, S. B. (2007). The impact of misspecifying the within-subject covariance structure in multiwave longitudinal multilevel models: A Monte Carlo study. Multivariate Behavioral Research, 42, 557-592.
17. McArdle, J. J., & Bell, R. Q. (2000). Recent trends in modeling longitudinal data by latent growth curve methods. In T. D. Little, K. U. Schnabel, & J. Baumert (Eds.), Modeling longitudinal and multiple-group data: Practical issues, applied approaches, and scientific examples (pp. 69-107). Mahwah, NJ: Lawrence Erlbaum Associates.
18. McArdle, J. J., & Epstein, D. (1987). Latent growth curves within developmental structural equation models. Child Development, 58, 110-133.
19. McArdle, J. J., & Woodcock, R. W. (1997). Expanding test-retest designs to include developmental time-lag components. Psychological Methods, 2, 403-435.
20. Meredith, W., & Tisak, J. (1984, July). On Tuckerizing curves. Paper presented at the annual meeting of the Psychometric Society, Santa Barbara, CA.
21. Meredith, W., & Tisak, J. (1990). Latent curve analysis. Psychometrika, 55, 107-122.
22. Muthén, L. K., & Muthén, B. O. (1998-2008). Mplus user's guide (5th ed.). Los Angeles, CA: Muthén & Muthén.
23. National Center for Education Statistics. (2001). User's manual for the ECLS-K public-use data files and electronic codebook. Washington, DC: U.S. Department of Education.
24. Ram, N., & Grimm, K. J. (2007). Using simple and complex growth models to articulate developmental change: Matching method to theory. International Journal of Behavioral Development, 31, 303-316.
25. Rogosa, D. R., & Willett, J. B. (1985). Understanding correlates of change by modeling individual differences in growth. Psychometrika, 50, 203-228.
26. Sivo, S., Fan, X., & Witta, L. (2005). The biasing effects of unmodeled ARMA time series processes on latent growth curve model estimates. Structural Equation Modeling, 12, 215-231.
27. Tisak, J., & Tisak, M. S. (1996). Longitudinal models of reliability and validity: A latent curve approach. Applied Psychological Measurement, 20, 275-288.
28. Willett, J. B., & Sayer, A. G. (1994). Using covariance structure analysis to detect correlates and predictors of individual change over time. Psychological Bulletin, 116, 363-381.
29. Wolfinger, R. D. (1993). Covariance structure selection in general mixed models. Communications in Statistics, Simulation and Computation, 22, 1079-1106.
30. Wolfinger, R. D. (1996). Heterogeneousvariance: Covariance structures for repeated measures. Journal of Agricultural, Biological, and Environmental Statistics, 1, 205-230.