Efficient resampling methods for nonsmooth estimating functions

Biostatistics

Volumn 9, Issue 2, 2008, Pages 355-363

  Zeng, Donglin ^a   Lin, D Y ^a  

^a University of North Carolina at Chapel Hill   (United States)

Author keywords

Bootstrap; Censoring; Quantile regression; Rank regression; Robustness; Variance estimation

Indexed keywords

ARTICLE; ATHEROSCLEROSIS; BIOMETRY; COMPUTER SIMULATION; EPIDEMIOLOGY; HUMAN; METHODOLOGY; MIDDLE AGED; MULTIPLE MYELOMA; PATHOPHYSIOLOGY; PREDICTION AND FORECASTING; RANDOMIZATION; REGRESSION ANALYSIS; REPRODUCIBILITY; SAMPLE SIZE; STANDARD; STATISTICAL ANALYSIS;

ATHEROSCLEROSIS; BIAS (EPIDEMIOLOGY); BIOMETRY; COMPUTER SIMULATION; DATA INTERPRETATION, STATISTICAL; HUMANS; MIDDLE AGED; MULTIPLE MYELOMA; PREDICTIVE VALUE OF TESTS; RANDOM ALLOCATION; REGRESSION ANALYSIS; REPRODUCIBILITY OF RESULTS; SAMPLE SIZE; WEIGHTS AND MEASURES;

EID: 41149102858     PISSN: 14654644     EISSN: 14684357     Source Type: Journal    
DOI: 10.1093/biostatistics/kxm034     Document Type: Article

References (20)

1. BUCHINSKY, M. (1995). Estimating the asymptotic covariance-matrix for quantile regression-models - a Monte Carlo study. Journal of Econometrics 68, 303-338.
2. CAI, T. X., PEPE, M. S., ZHENG, Y. Y., LUMLEY, T. AND JENNY, N. S. (2006). The sensitivity and specificity of markers for event times. Biostatistics 7, 182-197.
3. CHEN, Y. Q. AND JEWELL, N. P. (2001). On a general class of semiparametric hazards regression models. Biometrika 88, 687-702.
4. COX, D. R. AND OAKES, D. (1984). Analysis of Survival Data. London: Chapman and Hall.
5. EFRON, B. AND TIBSHIRANI, R. J. (1993). An Introduction to the Bootstrap. New York: Chapman and Hall.
6. HU, F. AND KALBFLEISCH, J. D. (2000). The estimating function bootstrap (with discussion). Canadian Journal of Statistics 28, 449-199.
7. HUBER, P. J. (1964). Robust estimation of a location parameter. The Annals of Mathematical Statistics 35, 73-101.
8. JIN, Z., LIN, D. Y., WEI, L. J. AND YING, Z. (2003). Rank-based inference for the accelerated failure time model. Biometrika 90, 341-353.
9. JIN, Z., LIN, D. Y. AND YING, Z. (2006). On the least squares regression with censored data. Biometrika 93, 147-162.
10. JIN, Z., YING, Z. AND WEI, L. J. (2001). A simple resampling method by perturbing the minimand. Biometrika 88, 381-390.
11. KALBFLEISCH, J. D. AND PRENTICE, R. L. (2002). The Statistical Analysis of Failure Time Data, 2nd edition. Hoboken, NJ: Wiley.
12. KOENKER, R. AND D'OREY, V. (1987). Computing regression quantiles. Applied Statistics 36, 383-393.
13. KRALL, J. M., UTHOFF, V. A. AND HARLEY, J. B. (1975). A step-up procedure for selecting variables associated with survival. Biometrics 31, 49-57.
14. LIN, D. Y. AND GEYER, C. J. (1992). Computational methods for semiparametric linear regression with censored data. Journal of Computational and Graphical Statistics 1, 77-90.
15. PARZEN, M. I., WEI, L. J. AND YING, Z. (1994). A resampling method based on pivotal estimating functions. Biometrika 81, 341-350.
16. THE ARIC INVESTIGATORS (1989). The Atherosclerosis Risk in Communities (ARIC) Study: design and objectives. American Journal of Epidemiology 129, 687-702.
17. TSIATIS, A. A. (1990). Estimating regression parameters using linear rank tests for censored data. The Annals of Statistics 18, 354-372.
18. VAN DER VAART, A. W. AND WELLNER, J. A. (1996). Weak Convergence and Empirical Processes. New York: Springer.
19. YAO, Q., WEI, L. J. AND HOGAN, J. W. (1998). Analysis of incomplete repeated measurements with dependent censoring times. Biometrika 85, 139-149.
20. YING, Z. (1993). A large sample study of rank estimation for censored regression data. The Annals of Statistics 21, 76-99.