JOURNAL BROWSE
Search
Advanced SearchSearch Tips
Comparing Imputation Methods for Doubly Censored Data
facebook(new window)  Pirnt(new window) E-mail(new window) Excel Download
 Title & Authors
Comparing Imputation Methods for Doubly Censored Data
Yoo, Han-Na; Lee, Jae-Won;
  PDF(new window)
 Abstract
In many epidemiological studies, the occurrence times of the event of interest are right-censored or interval censored. In certain situations such as the AIDS data, however, the incubation period which is the time between HIV infection and the diagnosis of AIDS is usually doubly censored. In this paper, we impute the interval censored HIV infection time using three imputation methods. Mid imputation, conditional mean imputation and approximate Bayesian bootstrap are implemented to obtain right censored data, and then Gibbs sampler is used to estimate the coefficient factor of the incubation period. By using Bayesian approach, flexible modeling and the use of prior information is available. We applied both parametric and semi-parametric methods for estimating the effect of the covariate and compared the imputation results incorporating prior information for the covariate effects.
 Keywords
Doubly censored data;conditional mean imputation;approximate Bayesian bootstrap;Gibbs sampler;
 Language
English
 Cited by
 References
1.
Arjas, E. and Gasbarra, D. (1994). Nonparametric Bayesian inference from right censored survival data, using the Gibbs sampler, Statistica Sinica, 4, 505-524

2.
Berliner, L. M. and Hill, B. M. (1988). Bayesian nonparametric survival analysis, Journal of the American Statistical Association, 83, 772-779 crossref(new window)

3.
Brookmeyer, R. and Goedert, J. (1989). Censoring in an epidemic with an application to hemophilia-associated AIDS, Biometrics, 45, 325-335 crossref(new window)

4.
Burridge, J. (1981). Empirical Bayes analysis of survival time data, Journal of the Royal Statistical Society, Series B, 43, 65-75

5.
De Gruttola, V. G. and Lagakos, S. W. (1989). Analysis of doubly-censored survival data, with application to AIDS, Biometrics, 45, 1-11 crossref(new window)

6.
Gauvreau, K., DeGruttola, V., Pagano, M. and Bellocco, R. (1994). Markers and incubation time: The effect of covariates on the induction time of AIDS using improved imputation of exact seroconversion times, Statistics in Medicine, 13, 2021-2030 crossref(new window)

7.
Geskus, R. B. (2001). Methods for estimating the AIDS incubation time distribution when date of seroconversion is censored, Statistics in Medicine, 20, 795-812 crossref(new window)

8.
Gomez, G. M. and Calle, M. L. (1999). Nonparametric estimation with doubly censored data, Journal of Applied Statistics, 26, 45-58 crossref(new window)

9.
Ibrahim, J. G., Chen, M. H. and Sinha, D. (2001). Bayesian Survival Analysis, Springer-Verlag, America

10.
Kalbfleisch, J. D. (1978). Nonparametric Bayesian analysis of survival time data, Journal of the Royal Statistical Society, Series B, 40, 214-221

11.
Kim, M. Y., De Gruttola, V. G. and Lagakos, S. W. (1993). Analyzing doubly censored data with covariates, with application to AIDS, Biometrics, .49, 13-22 crossref(new window)

12.
Law, C. G. and Brookmeyer, R. (1992). Effects of mid-point imputation on the analysis of doubly censored data, Statistics in Medicine, 11, 1569-1578 crossref(new window)

13.
Pan, W. (2000). A two-sample test with interval censored data via multiple imputation, Statistics in medicine, 19, 1-11 crossref(new window)

14.
Pan, W. (2001). A multiple imputation approach to regression analysis for doubly censored data with application to AIDS studies, Biometrics, 57, 1245-1250 crossref(new window)

15.
Rubin, D. B. (1987). Multiple Imputation for Nonresponse in Surveys, John Wiley & Sons, New York

16.
Sinha, D. and Dey, D. (1997). Semiparametric Bayesian analysis of survival data, Journal of the American Statistical Association, 92, Review paper

17.
Sun, J. (1995). Empirical estimation of a distribution function with truncated and doubly interval-censored data and its application to AIDS studies, Biometrics, 51, 1096-1104 crossref(new window)

18.
Sun, J. (2004). Statistical analysis of doubly interval-censored failure time data, In Handbook of Statistics 23: Advances in Survival Analysis (Eds., N. Balakrishnan and C. R. Rao), 105-122, North-Holland, Amsterdam, The Netherlands

19.
Sun, J., Liao, Q. and Pagano, M. (1999). Regression analysis of doubly censored failure time data with applications to AIDS studies, Biometrics, 55, 909-914 crossref(new window)

20.
Wellner, J. A. and Zhan, Y. (1997). A hybrid algorithm for computation of the nonparametric maximum likelihood estimator from censored data, Journal of the American Statistical Association, 92, 945-959 crossref(new window)