Simulation driven inferences for multiply imputed longitudinal datasets

Statistica Neerlandica

Volumn 58, Issue 4, 2004, Pages 466-482

  Demirtas, Hakan ^a  

^a UNIVERSITY OF ILLINOIS AT CHICAGO   (United States)

Author keywords

Linear mixed effects model; Longitudinal data; Missing data; Multiple imputation; Nonignorable dropout; Simulation

Indexed keywords

EID: 10944236293     PISSN: 00390402     EISSN: None     Source Type: Journal    
DOI: 10.1111/j.1467-9574.2004.00271.x     Document Type: Article

References (14)

1. COLLINS, L. M., J. L. SCHAFER and C. M. KAM (2001), A comparison of inclusive and restrictive strategies in modern missing-data procedures, Psychological Methods 6, 330-351.
2. GELFAND, A. E. and A. F. M. SMITH (1990), Sampling-based approaches to calculating marginal densities, Journal of the American Statistical Association 85, 398-409.
3. GILKS, W. R., S. RICHARDSON and D. J. SPIEGELHALTER (Eds) (1996), Markov chain Monte Carlo in practice, Chapman & Hall, London.
4. LAIRD, N. M. and J. H. WARE (1982), Random-effects model for longitudinal data, Biometrics 38, 963-974.
5. LITTLE, R. J. A. (1995), Modeling the dropout mechanism in longitudinal studies, Journal of the American Statistical Association 90, 1112-1121.
6. LITTLE, R. J. A. and D. B. RUBIN (2002), Statistical analysis with missing data, Wiley, New York.
7. MENG, X. L. (1994), Multiple imputation with uncongenial sources of input (with discussion), Statistical Science 9, 538-573.
8. RUBIN, D. B. (1976), Inference and missing data, Biometrika 63, 581-592.
9. RUBIN, D. B. (1987), Multiple imputation for nonresponse in surveys, John Wiley, New York.
10. RUBIN, D. B. (1996), Multiple imputation after 18 + years (with discussion), Journal of the American Statistical Association 91, 473-520.
11. SCHAFER, J. L. (1997), PAN: Multiple imputation for multivariate panel data software library for S-PLUS University Park PA. Technical report, The Pennsylvania State University, Department of Statistics.
12. SCHAFER, J. L. (1999), Multiple imputation: a primer, Statistical Methods in Medical Research 8, 3-15.
13. SCHAFER, J. L. and R. M. YUCEL (2002), Computational strategies for multivariate linear mixed-effects models with missing values, Journal of Computational and Graphical Statistics 11, 437-457.
14. VAN BUUREN, S., H. C. BOSHUIZEN and L. KNOOK (1999), Multiple imputation of missing blood pressure covariates in survival analysis, Statistics in Medicine 18, 681-694.