Mixed-effects models in the study of individual differences with repeated measures data

Multivariate Behavioral Research

Volumn 31, Issue 3, 1996, Pages 371-403

  Cudeck, Robert ^a  

^a UNIVERSITY OF MINNESOTA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 0030305195     PISSN: 00273171     EISSN: None     Source Type: Journal    
DOI: 10.1207/s15327906mbr3103_6     Document Type: Conference Paper

References (46)

1. Bock, R. D. (1983). The discrete Bayesian. In H. Wainer & S. Messick (Eds.), Principals of modern psychological measurement (pp. 103-115). Hillsdale, NJ: Erlbaum.
2. Bock, R. D. (1989). Measurement of human variation: A two-stage model. In R. D. Bock (Ed.), Multilevel analysis of educational data (pp. 319-342). San Diego: Academic Press.
3. Boyle, D. W., Hirst, K., Zerbe, G. O., Meschia, G. & Wilkening, R. B. (1990). Fetal hind limb oxygen consumption and blood flow during acute graded hypoxia. Pediatric Research, 28, 94-100.
4. Browne, M. W. (1993). Structured latent curve analysis. In C. M. Cuadras & C. R. Rao (Eds.), Multivariate analysis: Future directions 2 (pp. 171-197). Amsterdam: Elsevier Science.
5. Browne, M. W. & Du Toit, S. H. C. (1991). Models for learning data. In L. M. Collins & J. L. Horn (Eds.), Best methods for the analysis of change (pp. 47-68). Washington: American Psychological Association.
6. Bryk, A. S. & Raudenbush, S. W. (1992). Hierarchical linear models: Applications and data analysis methods. Newbury Park, CA: Sage.
7. Burchinal, M. & Appelbaum, M. I. (1991). Estimating individual developmental functions: Methods and their assumptions. Child Development, 62, 23-43.
8. Carroll, J. B. (1995). On methodology in the study of cognitive abilities. Multivariate Behavioral Research, 30, 429-452.
9. Crowder, M. J. & Hand, D. J. (1990). Analysis of repeated measures. London: Chapman & Hall.
10. Davidian, M. & Giltinan, D. M. (1993). Some simple methods for estimating intraindividual variability in nonlinear mixed effects models. Biometrics, 49, 59-73.
11. Davidian, M. & Giltinan, D. M. (1995). Nonlinear models for repeated measurement data. London: Chapman & Hall.
12. De Leeuw, J. & Kreft, I. (1986). Random coefficient models for multilevel analysis. Journal of Educational Statistics, 11, 57-85.
13. Diggle, P. J., Liang, K.-Y., & Zeger, S. L. (1994). Analysis of longitudinal data. Oxford: Oxford University Press.
14. Du Toit, M. (1996). The analysis of hierarchical and unbalanced complex survey data using multilevel models. Unpublished doctoral dissertation, University of Pretoria, Pretoria, South Africa.
15. Du Toit, S. H. C. (1993). Analysis of multilevel models. Part 1: Theoretical aspects. Pretoria, South Africa: Human Sciences Research Council.
16. Goldstein, H. (1987). Multilevel models in educational and social research. London: Griffin.
17. Goldstein, H. & McDonald, R. P. (1988). A general model for the analysis of multilevel data. Psychometrika, 53, 455-467.
18. Hirst, K., Boyle, D. W., Zerbe, G. O., & Wilkening, R. B. (1991). On nonlinear random effects models for repeated measurements. Communications in Statistics-Simulation, 20, 463-478.
19. Hovland, C. I. (1938). Experimental studies in rote-learning theory. Journal of Experimental Psychology, 23, 172-190.
20. Jennrich, R. I. & Schluchter, M. D. (1986). Unbalanced repeated-measures models with structured covariance matrices. Biometrics, 42, 805-820.
21. Jenss, R. M. & Bayley, N. (1937). A mathematical method for studying the growth of a child. Human Biology, 9, 556-563.
22. Kreft, G. G., De Leeuw, J., & Van der Leeden, R. (1994). Review of five multilevel analysis programs: BMDP-5V, GENMOD, HLM, ML3, VARCL. American Statistician, 48, 324-335.
23. Laird, N. M. (1988). Missing data in longitudinal studies. Statistics in Medicine, 7, 305-315.
24. Laird, N. M. & Ware, J. H. (1982). Random-effects models for longitudinal data. Biometrics, 38, 963-974.
25. Lewis, D. (1966). Quantitative methods in psychology. Iowa City, IA: University of Iowa.
26. Lindstrom, M. J. & Bates, D. M. (1990). Nonlinear mixed effects models for repeated measures data. Biometrics, 46, 673-687.
27. Longford, N. T. (1989). Fisher scoring algorithm for variance component analysis of data with multilevel structure. In R. D. Bock (Ed.), Multilevel analysis of educational data (pp. 297-310). San Diego: Academic Press.
28. Longford, N. T. (1993). Random coefficient models. Oxford: Oxford University Press.
29. McArdle, J. J. & Epstein, D. (1987). Latent growth curves within developmental structural equation models. Child Development, 58, 110-133.
30. McDonald, R. P. & Goldstein, H. (1989). Balanced versus unbalanced designs for linear structural relations in two-level data. British Journal of Mathematical and Statistical Psychology, 42, 215-232.
31. Meredith, W. & Tisak, J. (1990). Latent curve analysis. Psychometrika, 55, 107-122.
32. Morrell, C. H., Pearson, J. D., Carter, H. B., & Brant, L. J. (1995). Estimating unknown transition times using a piecewise nonlinear mixed-effects model in men with prostrate cancer. Journal of the American Statistician Association, 90, 45-53.
33. Muthén, B. O. (1994). Multilevel covariance structure analysis. Sociological methods and Research, 22, 376-398.
34. Muthén, B. O. & Satorra, A. (1989). Multilevel aspects of varying parameters in structural models. In R. D. Bock (Ed.), Multilevel analysis of educational data (pp. 87-99). New York: Academic.
35. Pinheiro, J. C. & Bates, D. M. (1995). Approximations to the loglikelihood function in the nonlinear mixed effects model. Journal of Computational and graphical Statistics, 4, 12-35.
36. Pinheiro, J. C., Bates, D. M., & Lindstrom, M. J. (1993). Nonlinear mixed effects classes and methods for S. Technical Report No. 931, Department of Statistics, University of Wisconsin.
37. Raudenbush, S. W. (1988). Educational applications of hierarchical linear models: A review. Journal of Educational Statistics, 13, 85-116.
38. Raudenbush, S. W. (1993). A crossed random effects model for unbalanced data with applications in cross-sectional and longitudinal research. Journal of Educational Statistics, 18, 321-349.
39. Rogosa, D. R., Brandt, D., & Zimowski, M. (1982). A growth curve approach to the measurement of change. Psychological Bulletin, 90, 726-748.
40. SAS Institute, Inc. (1985). SAS/IML user's guide, version 5 edition. Cary, NC: Author.
41. Schluchter, M. D. (1988). Analysis of incomplete multivariate data using linear models with structured covariance matrices. Statistics in Medicine, 7, 317-324.
42. Seber, G. A. F. & Wild, C. J. (1989). Nonlinear regression. New York: Wiley.
43. Tucker, L. R (1958). Determination of parameters of a functional relation by factor analysis. Psychometrika, 23, 19-23.
44. Vonesh, E. F. (1992). Non-linear models for the analysis of longitudinal data. Statistics in Medicine, 11, 1929-1954.
45. Vonesh, E. F. & Carter, R. L. (1992). Mixed-effects nonlinear regression for unbalanced repeated measures. Biometrics, 48, 1-17.
46. Woltz, D. J. (1988). An investigation of the role of working memory in procedural skill acquisition. Journal of Experimental Psychology: General, 117, 319-331.