Sample size and design considerations for phase II clinical trials with correlated observations

Controlled Clinical Trials

Volumn 20, Issue 3, 1999, Pages 242-252

  Sargent, Daniel J ^a   Sloan, Jeff A ^a   Cha, Steven S ^a  

^a MAYO CLINIC   (United States)

Author keywords

Correlated binomial; Multistage design

Indexed keywords

ARTICLE; CLINICAL TRIAL; COMPUTER SIMULATION; HUMAN; INFORMATION PROCESSING; METHODOLOGY; OBSERVATION; PHASE 2 CLINICAL TRIAL; SAMPLE; THEORY;

EID: 0032919164     PISSN: 01972456     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0197-2456(98)00058-0     Document Type: Article

References (22)

1. Emerich LJ. Common problems with statistical aspects of periodontal research papers. Periodontal Res 1990;61:206-208.
2. Palmer AK. Statistical analysis and choice of sample units. Teratology 1974;9:261-262.
3. Liang K-Y, McCullagh P. Case studies in binary dispersion. Biometrics 1993;49:623-630.
4. Rosner B. Statistical methods in ophthalmology: an adjustment for the intraclass correlation between eyes. Biometrics 1982;38:105-114.
5. Cox DR, Snell EJ. Analysis of Binary Data 2nd ed. London: Chapman and Hall; 1992.
6. Fleming TR. One-sample multiple testing procedures for phase II clinical trials. Biometrics 1982;43:143-151.
7. Simon R. Optimal two-stage designs for phase II clinical trials. Control Clin Trials 1989;10:1-10.
8. Green SI, Dahlberg S. Planned versus attained design in phase II clinical trials. Stat Med 1992;11:853-862.
9. Armitage P. Studies in the variability of pock counts. J Hygiene Camb 1957;55:564-581.
10. Bahadur RR. A representative of the joint distribution of responses to n dichotomous items. In: Soloman H, ed. Studies in Item Analysis and Prediction. Stanford: Stanford University Press; 1961.
11. Kupper LL, Haseman KJ. The use of a correlated binomial model for the analysis of certain toxicological experiments. Biometrics 1978;34:69-76.
12. Williams DA. The analysis of binary responses from toxicological experiments involving reproduction and teratogenicity. Biometrics 1975;31:949-952.
13. McCaughran DA, Arnold DW. Statistical models for numbers of implantation sites and embryonic deaths in mice. Toxicol Appl Pharmacol 1976;38:325-333.
14. McCullagh P, Nelder JA. Generalized Linear Models. London: Chapman and Hall; 1983.
15. Rosner B, Milton RC. Significance testing for correlated binary outcome data. Biometrics 1988;44:505-512.
16. Zucker D, Wittes J. Testing the effect of treatment in experiments with correlated binary outcomes. Biometrics 1992;48:695-710.
17. Liang K-Y, Zeger SL. Longitudinal data analysis using generalized linear models. Biometrika 1986;73:13-22.
18. Lipsitz SR, Laird NM, Harrington DP. Generalized estimating equations for correlated binary data: using the odds ratio as a measure of association. Biometrika 1991;78:153-160.
19. Qagish BF, Liang K-Y. Marginal models for correlated binary responses with multiple classes and multiple levels of nesting. Biometrics 1992;48:939-950.
20. Sharples K, Breslow N. Regression analysis of correlated binary data: some small sample results for the estimating equation approach. J Stat Comput Simul 1992;42:1-20.
21. Cohen J. Statistical Power Analysis for the Social and Behavioral Sciences. Hillsdale, NJ: Lawrence Erlbaum; 1988.
22. Park CG, Park T, Shin DW. A simple method for generating correlated binary variates. Am Stat 1996;50:306-310.