Directly parameterized regression conditioning on being alive: Analysis of longitudinal data truncated by deaths

Biostatistics

Volumn 6, Issue 2, 2005, Pages 241-258

  Kurland, Brenda F ^a   Heagerty, Patrick J ^a  

^a UNIVERSITY OF WASHINGTON   (United States)

Author keywords

Binary longitudinal data; Censoring; Dropout; Missing data

Indexed keywords

AGED; ARTICLE; BIOLOGICAL MODEL; COHORT ANALYSIS; DAILY LIFE ACTIVITY; DISABLED PERSON; FEMALE; HUMAN; LONGITUDINAL STUDY; MALE; MORTALITY; PATIENT; REGRESSION ANALYSIS; STATISTICAL MODEL; SURVIVAL;

ACTIVITIES OF DAILY LIVING; AGED; COHORT STUDIES; DISABLED PERSONS; FEMALE; HUMANS; LIKELIHOOD FUNCTIONS; LONGITUDINAL STUDIES; MALE; MODELS, BIOLOGICAL; MORTALITY; PATIENT DROPOUTS; REGRESSION ANALYSIS; SURVIVAL ANALYSIS;

EID: 22144491220     PISSN: 14654644     EISSN: None     Source Type: Journal    
DOI: 10.1093/biostatistics/kxi006     Document Type: Article

References (24)

1. BRAYNE, C., SPIEGELHALTER, D. J., DUFOUIL, C., CHI, L. Y., DENING, T. R., PAYKEL, E. S., O'CONNOR, D. W., AHMED, A., MCGEE, M. A. AND HUPPERT, F. A. (1999). Estimating the true extent of cognitive decline in the old old. Journal of the American Geriatrics Society 47, 1283-1288.
2. CROWDER, M. (1986). On consistency and inconsistency of estimating equations. Econometric Theory 2, 305-330.
3. DIEHR, P., PATRICK, D. L., SPERTUS, J., KIEFE, C. I., MCDONELL, M. AND FIHN, S. D. (2001). Transforming self-rated health and the SF-36 scales to include death and improve interpretability. Medical Care 39, 670-680.
4. DIGGLE, P. AND KENWARD, M. G. (1994). Informative drop-out in longitudinal data analysis (with discussion). Applied Statistics 43, 49-93.
5. FITZMAURICE, G. M. AND LAIRD, N. M. (2000). Generalized linear mixture models for handling nonignorable dropouts in longitudinal studies. Biostatistics 1, 141-156.
6. FRANGAKIS, C. E. AND RUBIN, D. B. (2002). Principal stratification in causal inference. Biometrics 58, 21-29.
7. GILL, T. M., DESAI, M. M., GAHBAUER, E. A., HOLFORD, T. R. AND WILLIAMS, C. S. (2001). Restricted activity among community-living older persons: incidence, precipitants, and health care utilization. Annals of Internal Medicine 135, 313-321.
8. GILL, T. M. AND KURLAND, B. F. (2003). The burden and patterns of disability in activities of daily living among community-living older persons. Journals of Gerontology Series A: Biological Sciences and Medical Sciences 58, 70-75.
9. GILL, T. M., WILLIAMS, C. S. AND TINETTI, M. E. (1999). The combined effects of baseline vulnerability and acute hospital events on the development of functional dependence among community-living older persons. Journals of Gerontology. Series A, Biological Sciences and Medical Sciences 54, M377-M383.
10. GRAY, S. M. AND BROOKMEYER, R. (2000). Multidimensional longitudinal data: estimating a treatment effect from continuous, discrete, or time-to-event response variables. Journal of the American Statistical Association 95, 396-406.
11. HAREL, O. (2003). Strategies for data analysis with two types of missing values, Ph.D. Thesis, The Pennsylvania State University Department of Statistics, University Park, PA.
12. HEAGERTY, P. J. (2002). Marginalized transition models and likelihood inference for longitudinal categorical data. Biometrics 58, 342-351.
13. HORVITZ, D. G. AND THOMPSON, D. J. (1952). A generalization of sampling without replacement from a finite universe. Journal of the American Statistical Association 47, 663-685.
14. LAIRD, N. M. (1988). Missing data in longitudinal studies. Statistics in Medicine 7, 305-315.
15. LIANG, K.-Y. AND ZEGER, S. L. (1986). Longitudinal data analysis using generalized linear models. Biometrika 73, 13-22.
16. LITTLE, R. J. A. AND RUBIN, D. B. (1987). Statistical Analysis with Missing Data. New York: John Wiley & Sons.
17. MILLER, M. E., TEN HAVE, T. R., REBOUSSIN, B. A., LOHMAN, K. K. AND REJESKI, W. J. (2001). A marginal model for analyzing discrete outcomes from longitudinal surveys with outcomes subject to multiple-cause nonresponse. Journal of the American Statistical Association 96, 844-857.
18. PAULER, D. K., MCCOY, S. AND MOINPOUR, C. (2003). Pattern mixture models for longitudinal quality of life studies in advanced stage disease. Statistics in Medicine 22, 795-809.
19. PEPE, M. S., HEAGERTY, P. AND WHITAKER, R. (1999). Prediction using partly conditional time-varying coefficients regression models. Biometrics 55, 944-950.
20. REVICKI, D. A., GOLD, K., BUCKMAN, D., CHAN, K., KALLICH, J. D. AND WOOLLEY, J. M. (2001). Imputing physical health status scores missing owing to mortality. Medical Care 39, 61-71.
21. RIBAUDO, H. J., THOMPSON, S. G. AND ALLEN-MERSH, T. G. (2001). A joint analysis of quality of life and survival using a random effect selection model. Statistics in Medicine 20, 1173-1184.
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. RUBIN, D. B. (1987). Multiple Imputation for Nonresponse in Surveys. New York: John Wiley & Sons.
24. SCHARFSTEIN, D. O., ROTNITZKY, A. AND ROBINS, J. M. (1999). Adjusting for nonignorable drop-out using semiparametric nonresponse models (with discussion). Journal of the American Statistical Association 94, 1096-1146.