Simultaneous inference for semiparametric nonlinear mixed-effects models with covariate measurement errors and missing responses

Biometrics

Volumn 63, Issue 2, 2007, Pages 342-350

  Liu, Wei ^a   Wu, Lang ^a  

^a UNIVERSITY OF BRITISH COLUMBIA   (Canada)

Author keywords

Cubic spline basis; Longitudinal data; Monte Carlo EM algorithm; Random effects model

Indexed keywords

MEASUREMENT ERRORS; RANDOM ERRORS; RANDOM PROCESSES;

COVARIATE MEASUREMENT ERRORS; CUBIC SPLINE; CUBIC SPLINE BASE; LONGITUDINAL DATA; MIXED EFFECTS MODELS; MONTE CARLO EM ALGORITHM; NONLINEAR MIXED EFFECTS; RANDOM EFFECTS MODEL; SEMIPARAMETRIC; SPLINE-BASIS;

INFERENCE ENGINES;

COVARIANCE ANALYSIS; ERROR ANALYSIS; MEASUREMENT METHOD; SIMULATION;

ARTICLE; COVARIANCE; DATA ANALYSIS; INTERMETHOD COMPARISON; LONGITUDINAL STUDY; MEASUREMENT ERROR; SEMIPARAMETRIC NONLINEAR MIXED EFFECT; SIMULATION; STATISTICAL MODEL; STATISTICAL PARAMETERS;

EID: 34547679633     PISSN: 0006341X     EISSN: 15410420     Source Type: Journal    
DOI: 10.1111/j.1541-0420.2006.00687.x     Document Type: Article

References (19)

1. Carroll, R. J., Ruppert, D., and Stefanski, L. A. (1995). Measurement Error in Nonlinear Models. London : Chapman and Hall.
2. Davidian, M. and Giltinan, D. M. (1995). Nonlinear Models for Repeated Measurements Data. London : Chapman & Hall.
3. Diggle, P. and Kenward, M. G. (1994). Informative drop-out in longitudinal data analysis (with discussion). Applied Statistics 43, 49 93.
4. Gelfand, A. E., Sahu, S. K., and Carlin, B. P. (1996). Efficient parameterizations for generalized linear models (with discussion). Bayesian Statistics 5, 165 180.
5. Grossman, Z., Polis, M., Feinberg, M. B., et al 1999). Ongoing HIV dissemination during HAART. Nature Medicine 5, 1099 1103.
6. Higgins, K. M., Davidian, M., and Giltinan, D. M. (1997). A two-step method to measurement error in time-dependent covariates in nonlinear mixed-effects models, with application to IGF-I pharmacokinetics. Journal of the American Statistical Association 92, 436 448.
7. Ibrahim, J. G., Chen, M. H., and Lipsitz, S. R. (2001). Missing responses in generalized linear mixed models when the missing data mechanism is nonignorable. Biometrika 88, 551 564.
8. Ke, C. and Wang, Y. (2001). Semiparametric nonlinear mixed-effects models and their applications (with discussions). Journal of the American Statistical Association 96, 1272 1298.
9. Lindstrom, M. J. and Bates, D. M. (1990). Nonlinear mixed effects models for repeated measures data. Biometrics 46, 673 687.
10. Little, R. J. A. (1995). Modeling the drop-out mechanism in repeated measures studies. Journal of the American Statistical Association 90, 1112 1121.
11. Liu, W. and Wu, L. (2005). Semiparametric nonlinear mixed-effects models with covariate measurement errors. Technical Report, Department of Statistics, University of British Columbia, Canada.
12. Louis, T. A. (1982). Finding the observed information matrix when using the EM algorithm. Journal of the Royal Statistical Society, Series B 44, 226 233.
13. McLachlan, G. J. and Krishnan, T. (1997). The EM Algorithm and Extensions. New York : Wiley.
14. Rice, J. A. and Wu, C. O. (2001). Nonparametric mixed-effects models for unequally sampled noisy curves. Biometrics 57, 253 259.
15. Shah, A., Laird, N., and Schoenfeld, D. (1997). A random-effects model for multiple characteristics with possibly missing data. Journal of the American Statistical Association 92, 775 779.
16. Vonesh, E. F., Wang, H., Nie, L., and Majumdar, D. (2002). Conditional second-order generalized estimating equations for generalized linear and nonlinear mixed-effects models. Journal of the American Statistical Association 97, 271 283.
17. Wei, G. C. and Tanner, M. A. (1990). A Monte Carlo implementation of the EM algorithm and the poor man's data augmentation algorithm. Journal of the American Statistical Association 85, 699 704.
18. Wu, L. (2002). A joint model for nonlinear mixed-effects models with censoring and covariates measured with error, with application to AIDS studies. Journal of the American Statistical Association 97, 955 964.
19. Wu, H. and Zhang, J. (2002). The study of long-term HIV dynamics using semi-parametric non-linear mixed-effects models. Statistics in Medicine 21, 3655 3675.