Latent variable model for joint analysis of multiple repeated measures and bivariate event times

Journal of the American Statistical Association

Volumn 96, Issue 455, 2001, Pages 906-914

  Huang, Wenzheng ^a   Zeger, Scott L ^b   Anthony, James C ^b   Garrett, Elizabeth ^c  

^a HARVARD SCHOOL OF PUBLIC HEALTH   (United States)

^b JOHNS HOPKINS BLOOMBERG SCHOOL OF PUBLIC HEALTH   (United States)

^c JOHNS HOPKINS UNIVERSITY   (United States)

Author keywords

Automatic differentiation; Failure time analysis; Latent variable; Longitudinal data analysis; Missing data; Prevention research

Indexed keywords

EID: 0442280678     PISSN: 01621459     EISSN: 1537274X     Source Type: Journal    
DOI: 10.1198/016214501753208609     Document Type: Article

References (26)

1. Baker, S. G. (1994), “Regression Analysis of Grouped Survival Data With Incomplete Covariates: Nonignorable Missing-Data and Censoring Mechanisms,” Biometrics, 50, 821–826.
2. Bartholomew, D. J. (1987), Latent Variables Models and Factor Analysis, London: Griffin.
3. Bollen, K. A. (1989), Structural Equations Modeling With Latent Variables, New York: Wiley.
4. Chilcoat, H. D., and Anthony, J. C. (1996), “Impact of Parent Monitoring on Initiation of Drug Use Through Later Childhood,” Journal of the American Academy of Child and Adolescence Psychiatry, 35, 91–100.
5. De Gruttola, V., and Tu, X. M. (1994), “Modelling Progression of CD-4 Lymphocyte Count and Its Relationship to Survival Time,” Biometrics, 50, 1003–1014.
6. Dempster, A. P., Laird, N. M., and Rubin, D. B. (1977), “Maximum Likelihood Estimation From Incomplete Data via the EM Algorithm” (with discussion), Journal of the Royal Statistical Society, Ser. B, 39, 1–38.
7. Diggle, P., and Kenward, M. G. (1994), “Informative Drop-out in Longitudinal Data Analysis,” Applied Statistics, 43, 49–93.
8. Fischer, G. H. (1976), “Linear Logistic Latent Trait Models: Theory and Application,” in Structural Models of Thinking and Learning, eds. H. Sapda and W. F. Kempf, Bern: Huber, pp. 203–225.
9. Follman, D., and Wu, M. C. (1995), “An Approximate Generalized Linear Model With Random Effects For Informative Missing Data,” Biometrics, 51, 151–186.
10. Griewank, A., and Corliss, G. F. (1991), Automatic Differentiation of Algorithm: Theorem, Implementation, and Application, Philadelphia: S IAM.
11. Haberman, S. J. (1979), Analysis of Qualitative Data, Vol. 2, New York: Academic.
12. Heagerty, P. J., and Zeger, S. L. (1997), “Lorelogram: A Regression Approach to Exploring Dependence in Longitudinal Categorical Responses,” Journal of American Statistical Association, 93, 150–162.
13. Hogan, J. W., and Laird, N. M. (1997), “Mixture Models for the Joint Distribution of Repeated Measures and Event Times,” Statistics in Medicine, 16, 239–257.
14. Jamshidian, M., and Jennrich, R. (2000), “Standard Errors for EM Estimation,” Journal of the Royal Statistical Society, Ser. B, 62, 257–270.
15. Kellam, S. G., and Anthony, J. C. (1998), “Targeting Early Antecedents to Prevent Tobacco Smoking: Findings From an Epidemiologically Based Randomized Field Trial,” American Journal of Public Health, 88, 1490–1495.
16. Kellam, S. G., and Rebok, G. W. (1992), “Building Developmental and Etiological Theory Through Epidemiologically Based Preventive Intervention Trials,” in Preventing Antisocial Behavior: Interventions from Birth Through Adolescence, eds. J. M. McCord and R. E. Tremblay, New York: Guilford, pp. 162–195.
17. Lipsitz, S. R., Laird, N. M., and Harrington, D. P. (1991), “Generalized Estimating Equations for Correlated Binary Data: Using the Odds Ratio as a Measure of Association,” Biometrika, 78, 153–160.
18. Little, R. J. A. (1995), “Modeling the Drop-out Mechanism in Repeated-Measures Studies,” Journal of American Statistical Association, 90, 1112–1121.
19. Little, R. J. A, and Rubin, D. B., (1987), Statistical Analysis With Missing Data, New York: Wiley.
20. Louis, T. A. (1982), “Finding the Observed Information Matrix When Using the EM Algorithm,” Journal of the Royal Statistical Society, Ser. B, 44, 226–233.
21. Meng, X. L., and Rubin, D. B. (1991), “Using EM to Obtain Asymptotic Variance-Covariance Matrices: The SEM algorithm,” Journal of the American Statistical Association, 86, 899–909.
22. Robins, J. M., Rotnitzky, A., and Zhao, L. P. (1995), “Analysis of Semiparametric Regression Models for Repeated Outcomes in the Presence of Missing Data,” Journal of the American Statistical Association, 90, 106–121.
23. Woodbury, M. A., and Manton, K. G. (1989), “Grade of Membership Analysis of Depression-Related Psychiatric Disorders,” Sociological Methods and Research, 18, 126–163.
24. Wu, L. T., and Anthony, J. C. (1999), “Tobacco Smoking and Depressed Mood in Late Childhood and Early Adolescence,” American Journal of Public Health, 89, 1837–1840.
25. Wu, M. C., and Carroll, R. J. (1988), “Estimation and Comparison of Changes in the Presence of Informative Right Censoring by Modeling the Censoring Process,” Biometrics, 44, 175–188.
26. Wulfsohn, M. S., and Tsiatis, A. A. (1997), “A Joint Model for Survival and Longitudinal Data Measured with Error,” Biometrics, 53, 330–339.