Multiple comparisons and multiple contrasts in randomized dose-response trials - Confidence interval oriented approaches

Journal of Biopharmaceutical Statistics

Volumn 16, Issue 5, 2006, Pages 711-731

  Hothorn, Ludwig A ^a  

^a LEIBNIZ UNIVERSITY HANNOVER   (Germany)

Author keywords

Multiple contrasts; Randomized dose finding trials; Simultaneous confidence intervals; Trend test

Indexed keywords

ACONIAZIDE; ANTIANGINA PECTORIS AGENT; AZIDE; HYPOCHOLESTEROLEMIC AGENT; NEW DRUG; PLACEBO; UNCLASSIFIED DRUG;

ARTICLE; CLINICAL TRIAL; COMPARATIVE STUDY; CONFIDENCE INTERVAL; CONTROLLED CLINICAL TRIAL; CONTROLLED STUDY; DOSE CALCULATION; DOSE RESPONSE; DRUG EFFICACY; DRUG SAFETY; HUMAN; HYPOTHESIS; MAXIMUM TOLERATED DOSE; NONHUMAN; PRACTICE GUIDELINE; PRIORITY JOURNAL; RANDOMIZED CONTROLLED TRIAL;

ALGORITHMS; CONFIDENCE INTERVALS; DOSE-RESPONSE RELATIONSHIP, DRUG; DRUG THERAPY; HUMANS; LIKELIHOOD FUNCTIONS; MODELS, STATISTICAL; PLACEBOS; RANDOMIZED CONTROLLED TRIALS; RESEARCH DESIGN; TREATMENT OUTCOME;

EID: 33751578255     PISSN: 10543406     EISSN: 15205711     Source Type: Journal    
DOI: 10.1080/10543400600860576     Document Type: Article

References (51)

1. Bartholomew, D. J. (1961). Ordered tests in the analysis of variance. Biometrika 48:325-332.
2. Bauer, P., Roehmel, J., Maurer, W., Hothorn, L. A., Lehmacher, W. (1998). Testing strategies in multi-dose experiments including active control. Stat. Med. 17:2133-2146.
3. Bauer, P., Brannath, W., Posch, M. (2001). Multiple testing for identifying effective and safe treatments. Biometr. J 43:605-616.
4. Bradu, D., Gabriel, K. R. (1974). Simultaneous statistical inference on interaction in 2-way analysis of variance. J. Am. Stat. Assoc. 69:428-436.
5. Bretz, F. (1999). Powerful Modifications of Williams Test on Trend. Ph.D. thesis, University of Hannover. (Available at http://www.bioinf.uni-hannover. de)
6. Bretz, F., Hothorn, L. A. (2000). A powerful alternative to Williams test with application to toxicological dose-response relationships of normally distributed data. Environm. Ecol. Stat. 7:135-154.
7. Bretz, F., Seidel, D. (2000). SAS/IML programs for exact calculations of orthant probabilities for arbitrary dimensions. Comput. Stat. Data Anal. 33:220-221.
8. Bretz, F., Hothorn, L. A. (2001). Testing dose-response relationships with a priori unknown possibly nonmonotone shapes. J. Biopharm. Stat. 11:193-207.
9. Bretz, F., Hothorn, L. A. (2003). Statistical analysis of monotone or non-monotone dose-response data from in vitro toxicological assays. ATLA-Altern. Lab. Anim. 31:81-96 Suppl. 1.
10. Bretz, F., Hothorn, L. A., Hsu, J. C. (2003). Identifying effective and/or safe doses by stepwise confidence intervals for ratios. Stat. Med. 22:847-858.
11. Bretz, F., Hothorn, T. Westfall, P. (2002). On multiple comparisons in R. R-news 3:14-17.
12. Bretz, F., Pinheiro, I. C., Branson, M. (2005). Combining multiple comparisons and modeling techniques in dose-response studies. Biometrics 61:738-748.
13. Center for Drug Evaluation and Research (1994). Guideline for Industry: Dose-Response Information to Support Drug Registration. Rockville, MD: U.S. Food and Drug Administration. (Available at http://www.fda.gov/cder/guidance/iche4. pdf)
14. Channon, E. J., McEntegart, D. J. (2001). Confidence intervals and p-values for Williams' and other step-down multiple comparison tests against control. J. Biopharm Stat. 11:45-63.
15. Chen, J. J., Kodell, R. L., Gaylor, D. W. (1996). Risk assessment for nonquantal effects. In: Fan, A. M., Chang, L. W., eds. Toxicology and Risk Assessment. New York: Marcel Dekker, pp. 503-513.
16. Combes, R. D. (1997). Statistical analysis of dose-response data from in vitro assays: an illustration using Salmonella mutagenicity data. Toxicol. in Vitro 11:683-687.
17. Committee for Proprietary Medicinal Products (2002). Points to Consider on Multiplicity Issues in Clinical Trials. London: The European Agency for the Evaluation of Medicinal Products.
18. Dilba, G. (2005). Simultaneous Inference for Ratio of Location Parameters. Ph.D. thesis, University of Hannover.
19. Dilba, G., Schaarschmidt, F. (2005). The R Package mratios Constructing Simultaneous Confidence Intervals for Ratio-to-Control. Biostatistics Unit, University of Hannover. (Available at http://www.bioinf.uni-hannover.de).
20. Dilba, G., Bretz, F., Guiard, V., Hothorn, L. A. (2004). Simultaneous confidence intervals for ratios with application to the comparison of several treatments with a control. Methods Inf. Med. 43:465-469.
21. Dilba, G., Bretz, F., Guiard, V. (2006a). Simultaneous confidence sets and confidence intervals for multiple ratios. J. Stat. Plann. Inf. 36:2640-2658.
22. Dilba, G., Bretz, F., Hothorn, L. A., Guiard, V. (2006b). Power and sample size computations for simultaneous tests for non-inferiority and equivalence trials with inferences based on the ratio of means. Stat. Med. 25:1131-1147.
23. Dunnett, C. W. (1955). A multiple comparison procedure for comparing several treatments with a control. J. Amer. Statist. Assoc. 50:1096-1121.
24. Fieller, E. (1954). Some problems in interval estimation. J. R. Stat. Soc. B16:175-185.
25. Finner, H., Strassburger, K. (2002). The partitioning principle: a powerful tool in multiple decision theory. Ann. Stat. 30:1194-1213.
26. Hauschke, D., Kieser, M. (2001). Multiple testing to establish non-inferiority of k treatments with a reference based on the ratio of two means. Drug Inform. J. 35:1247-1251.
27. Hirotsu, C. (1997). Isotonic inference with particular interest in application to clinical trials. In: Kitsos, C. P., Edler, L., eds. Industrial Statistics. Heidelberg, Germany: Physica-Verlag, pp. 233-241.
28. Hochberg, Y., Tamhane, A. C. (1987). Probability and Mathematical Statistics: Multiple Comparison Procedures. New York: John Wiley & Sons.
29. Hothorn, L. A. (2003). Statistics of interlaboratory in vitro toxicological studies. ATLA-Altern. Lab. Anim. 31:43-63, Suppl. 1.
30. Hothorn, L. A. (2004). A robust statistical procedure for evaluating genotoxicity data. Environmetrics 15:635-641.
31. Hothorn, L. A., Bretz, F. (2000). One-sided simultaneous confidence intervals for effective dose steps in unbalanced designs. Biometr. J. 42:995-1006.
32. Hothorn, L. A., Hauschke, D. (2000). Identifying the maximum safe dose: a multiple testing approach. J. Biopharm. Stat. 10:15-30.
33. Hothorn, L. A., Wassmer, G. (2003). Analyzing randomized dose finding studies with a primary and a secondary endpoint. J. Biopharm. Stat. 13:301-305.
34. Hsu, J. C., Berger, R. L. (1999). Stepwise confidence intervals without multiplicity adjustment for dose-response and toxicity studies. J. Am. Stat. Assoc. 94:468-482.
35. Jan, S. L., Chen, Y. I. (2004). Nonparametric procedures for simultaneous identification of the minimum effective dose in each of several groups. J. Biopharm. Stat. 14:781-789.
36. Kong, L., Koch, G., Liu, T. (2005). Performance of some multiple testing procedures to compare three doses of a test drug and placebo. Pharm. Stat. 4:25-35.
37. Liu, W., Miwa, T., Hayter, A. J. (2000). Simultaneous confidence interval estimation for successive comparisons of ordered treatment effects. J. Stat. Plann. Inf. 88:75-86.
38. Marcus, R. (1976). The power of some tests of the equality of normal means against an ordered alternative. Biometrika 63:177-183.
39. Marcus, R., Genizi, A. (1994). Simultaneous confidence intervals for umbrella contrasts of normal means. Comput. Stat. Data Anal. 17:393-407.
40. Neuhaeuser, M., Hothorn, L. A. (1997). Trend tests for dichotomous endpoints with application in carcinogenicity studies. Drug Inform. J. 30:463-469.
41. R Development Core Team (2004). The R Project for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing. (available at http://www.R-project.org).
42. Robertson, T., Wright, F. T., Dykstra, R. L. (1988). Order Restricted Statistical Inference. New York: John Wiley & Sons.
43. Stewart, W. H., Ruberg, S. J. (2000). Detecting dose response with contrasts. Stat. Med. 19:913-921.
44. Tamhane, A. C., Logan, B. R. (2002). Multiple test procedures for identifying the minimum effective and maximum safe doses of a drug. J. Am. Stat. Assoc. 97:293-301.
45. Tamhane, A. C., Logan, B. R. (2004). Finding the maximum safe dose level for heteroscedastic data. J. Biopharm. Stat. 14:843-856.
46. Tamhane, A. C., Hochberg, Y., Dunnett, C. W. (1996). Multiple test procedures for dose finding. Biometrics 52:21-37.
47. Tamhane, A. C., Dunnett, C. W., Green, J. W., Wetherington, J. D. (2001). Multiple test procedures for identifying the maximum safe dose. J. Am. Stat. Assoc. 96:835-843.
48. U.S. Food and Drug Administration (1998) Guidance for Industry: E9 Statistical Principles for Clinical Trials. Rockville, MD: FDA. (available at http://www.fda.gov/cder/guidance/ICH_E9-fnl.PDF).
49. Westfall, P. H., Young, S. S. (1993). Resampling-Based Multiple Testing: Examples and Methods for p-Value Adjustment. New York: John Wiley & Sons.
50. Westfall, P. H., Tobias, R. D., Rom, D. (1999). Multiple comparisons and multiple tests. Cary, NC: SAS.
51. Williams, D. A. (1972). The comparison of several dose levels with a zero dose control. Biometrics 28:519-531.