Testing independence for bivariate current status data

Journal of the American Statistical Association

Volumn 99, Issue 465, 2004, Pages 145-155

  Ding, A Adam ^a   Wang, Weijing ^b  

^a NORTHEASTERN UNIVERSITY   (United States)

^b NATIONAL CHIAO TUNG UNIVERSITY   (Taiwan)

Author keywords

Cochran Mantel Haenszel test; Epidemiology; Interval censoring; Lifetime data; Nonparametric analysis; Two by two table

Indexed keywords

EID: 2142683035     PISSN: 01621459     EISSN: 1537274X     Source Type: Journal    
DOI: 10.1198/016214504000000142     Document Type: Article

References (24)

1. Agresti, A. (1990), Categorical Data Analysis, New York: Wiley.
2. Anderson, J. E., Louis, T. A., Holm, N. V., and Harvald, B. (1992), “Time-Dependent Association Measures for Bivariate Survival Distributions,” Journal of the American Statistical Association, 87, 641–650.
3. Ayer, M., Brunk, H. D., Ewing, G. M., Reid, W. T., and Silverman, E. (1955), “An Empirical Distribution Function for SamplingWith Incomplete Observations,” The Annals of Mathematical Statistics, 26, 641–647.
4. Clayton, D. G. (1978), “A Model for Association in Bivariate Life Tables and Its Application in Epidemiological Studies of Familial Tendency in Chronic Disease Incidence,” Biometrika, 65, 141–151.
5. Dabrowska, D. M. (1988), “Kaplan–Meier Estimates on the Plane,” The Annals of Statistics, 16, 1475–1489.
6. Dudley, R. M. (1987), “Universal Donsker Classes and Metric Entropy,” The Annals of Probility, 15, 1306–1326.
7. Finkelstein, D. M. (1986), “A Proportional Hazards Model for Interval-Censored Failure Time Data,” Biometrics, 42, 845–854.
8. Genest, C. (1987), “Frank’s Family of Bivariate Distributions,” Biometrika, 74, 549–555.
9. Groeneboom, P., and Wellner, J. A. (1992), Information Bounds and Non-Parametric Maximum Likelihood Estimation, Boston: Birkhäuser.
10. Hsu, L., and Prentice, R. L. (1996), “A Generalization of the Mantel–Haenszel Tests to Bivariate Failure Time Data,” Biometrika, 83, 905–911.
11. Huang, J., and Wellner, J. A. (1995), “Asymptotic Normality of the NPMLE of Linear Functionals for Interval Censored Data, Case 1,” Statistica Neeriandica, 49, 153–163.
12. Lin, D. Y., Oakes, D., and Ying, Z. (1998), “Additive Hazards Regression With Current Status Data,” Biometrika, 85, 289–298.
13. Oakes, D. (1982), “A Concordance Test for Independence in the Presence of Bivariate Censoring,” Biometrics, 38, 451–455.
14. Peto, R. (1973), “Experimental Survival Curves for Interval-Censored Data,” Journal of Applied Statistics, 22, 86–91.
15. Prentice, R. L., and Cai, J. (1992), “Covariance and Survivor Function Estimation Using Censored Multivariate Failure Time Data,” Biometrika, 79, 495–512.
16. Rabinowitz, D., Tsiatis, A., and Aragon, J. (1995), “Regression With Interval Censored Data,” Biometrika, 82, 501–513.
17. Rossini, A. J., and Tsiatis, A. A. (1996), “A Semiparametric Proportional Odds Regression Model for the Analysis of Current Status Data,” Journal of the American Statistical Association, 91, 713–721.
18. Sheehy, A., and Wellner, J. A. (1992), “Uniform Donsker Classes of Functions,” The Annals of Probability, 20, 1983–2030.
19. Shih, J. H., and Louis, T. A. (1996), “Tests of Independence for Bivariate Survival Data,” Biometrics, 52, 1440–1449.
20. Turnbull, B. W. (1976), “The Empirical Distribution Function With Arbitrarily Grouped, Censored and Truncated Data,” Journal of the Royal Statistical Society, Ser. B, 38, 290–295.
21. van der Laan, M. J., and Robbins, J. M. (1998), “Locally Efficient Estimation With Current Status Data and Time-Dependent Covariates,” Journal of the American Statistical Association, 93, 693–701.
22. Wand, M. P., and Jones, M. C. (1995), Kernel Smoothing, London: Chapman & Hall.
23. Wang, W., and Ding, A. A. (2000), “On Assessing the Association for Bivariate Current Status Data,” Biometrika, 87, 879–893.
24. Wang, W., and Wells, M. T. (2000), “Nonparametric Estimation of Kendell’s Tau Under Censoring,” Statistica Sinica, 10, 1199–1215.