On the bias of estimation of a Brownian motion drift following group sequential tests

Statistica Sinica

Volumn 9, Issue 4, 1999, Pages 923-937

  Li, Zhengqing ^a   DeMets, David L ^b  

^a Dept of Biometry and Statistics ^*  (United States)

^b UNIVERSITY OF WISCONSIN MADISON   (United States)

Author keywords

Alpha spending function; Interim analysis; Maximum likelihood; Robustness; Stopping time

Indexed keywords

EID: 0033262353     PISSN: 10170405     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (23)

1. Armitage, P., McPherson, C. K. and Rowe, B. C. (1969). Repeated significance tests on accumulating data. J. Roy. Statist. Soc. Ser. A 132, 235-244.
2. Chang, M. N. (1989). Confidence intervals for a normal mean following a group sequential test. Biometrics 45, 247-254.
3. DeMets, D. L. and Ware, J. H. (1980). Group sequential methods for clinical trials with a one-sided hypothesis. Biometrika 67, 651-660.
4. DeMets, D. L. and Ware, J. H. (1982). Asymmetric group sequential boundaries for monitoring clinical trials. Biometrika 69, 661-663.
5. Emerson, S. and Fleming, T. R. (1990). Parameter estimation following group sequential hypothesis testing. Biometrika 77, 875-892.
6. Gange, S. J. (1994). Multivariate ordinal responses in clinical trials. Ph.D. thesis, University of Wisconsin-Madison.
7. Hughes, M. D., Freedman, L. and Pocock, S. J. (1992). The impact of stopping rules on hetero-geneity of results in overview of clinical trials. Biometrics 48, 41-53.
8. Hughes, M. D. and Pocock, S. J. (1988). Stopping rules and estimation problems in clinical trials. Statistics in Medicine 7, 1231-1242.
9. Kim, K. and DeMets, D. L. (1987). Design and analysis of group sequential tests based on the type I error spending rate function. Biometrika 74, 149-154.
10. Lan K. K. G. and DeMets, D. L. (1983). Discrete sequential boundaries for clinical trials. Biometrika 70, 659-663.
11. Lan, K. K. G. and Zucker, D. (1993). Sequential monitoring of clinical trials: the role of information in Brownian motion. Statistics in Medicine 12, 753-765.
12. Lee, J. W. and DeMets, D. L. (1991). Sequential comparison of change with repeated measurement data. J. Amer. Statist. Assoc. 86, 757-762.
13. O'Brien, P. C. and Fleming, T. R. (1979). A multiple testing procedure for clinical trials. Biometrics 35, 549-556.
14. Pinheiro, J. C. and DeMets, D. L. (1995). Estimating and reducing bias in group sequential designs with Gaussian independent increment structure. Technical Report 96, Department of Biostatistics, University of Wisconsin-Madison.
15. Pocock, S. J. (1977). Group sequential methods in the design and analyses of clinical trials. Biometrika 64, 191-199.
16. Pocock, S. J. and Hughes, M. D. (1989). Practical problems in interim analyses with particular regard to estimation. Controlled Clinical Trials 10, 209s-221s.
17. Reboussin, D. M., DeMets, D. L., Kim, K and Lan, K. K. G. (1995). Programs for computing group sequential bounds using the Lan-DeMets method. Technical Report 95, Department of Biostatistics, University of Wisconsin-Madison.
18. Siegmund, D. (1978). Estimation following sequential tests. Biometrika 65, 341-349.
19. Todd, S., Whitehead, J. and Facey, K. M. (1996). Point and interval estimation following a sequential clinical trial. Biometrika 83, 453-461.
20. Tsiatis, A. A., Boucher, H. and Kim, K. (1995). Sequential methods for parametric survival models. Biometrika 82, 165-173.
21. Tsiatis, A. A., Rosner, G. L. and Mehta, C. R. (1984). Exact confidence intervals following a group sequential tests. Biometrics 40, 797-803.
22. Whitehead, J. (1986). On the bias of maximum likelihood estimation following a sequential test. Biometrika 73, 573-581.
23. Woodroofe, M. (1992). Estimation after sequential testing: a simple approach for a truncated sequential probability ratio test. Biometrika 79, 347-353.