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Unformatted text preview: PubH 7420 Clinical Trials: Readings for Week 8 1. Halperin, M., Rogot, E., Gurian, J., Ederer, F.: Sample sizes for medical trials with specific reference to long-term therapy. J. Chronic Dis., 21:13-24, 1968. 2. Friedman, Furberg, and DeMets. Fundamentals of Clinical Trials. Chapter 7. Supplemental Reading/References 1. Wu, M., Fisher, M., DeMets, D. Sample sizes for long term medical trials with time-dependent dropout and event rates. Cont. Clinical Trials , 1, 109-121, 1980. 2. Lachin, JM. Introduction to sample size determination and power analysis for clinical trials. Cont. Clinical Trials , 2, 93-113, 1981. 3. Lakatos, E., Sample sizes based on the log-rank statistic in complex clinical trials. Biometrics 44:229-241, 1988. 4. Shih, J., Sample size estimation for complex clinical trials. Cont. Clinical Trials , 16:395- 407, 1996. 5. Farrington CP, Manning G. Test statistics and sample size formulae for comparative binomial trials with null hypothesis of non-zero risk difference and non-unity relative risk. Stat Med 9:1447-1454, 1990. 6. Tamayo-Sarver, JH, Albert JM, Tamayo-Sarver M, Cydulka RK. How to determine whether your intervention is different, at least as effective as, or equivalent: a basic introduction. Acad Emerg Med 2005;12:536-542. 7. Whitehead J. Sample size calculations for ordered categorical data. Stat Med 12:2257- 2271, 1993. 8. http://www.bio.ri.ccf.org/power .html 9. Frieman et al. The importance of beta, the type II error and sample size in the design and interpretation of the randomized control trial. NEJM 299:690-694, 1978. 10. Moher D, Dulberg CS, Wells GA. Statistical power, sample, size, and their reporting in randomized controlled trials. JAMA 272, 122-124, 1994. 11. Meinert C. Clinical Trials: Design, Conduct and Analysis. Chapter 9. 1 Sample Size Estimation Estimation of sample size is one of the most common questions posed of statisticians, yet it is almost entirely a non-statistical exercise. The following are important points to remember: 1. Sample size should be specified in advance of the study; the number is usually determined by the primary objective of the study; 2. Sample size estimation required knowledge of the subject area and collaboration; 3. Sample size should account for non-compliance and withdrawal from the study because the primary analysis should be intent-to-treat.. 4. Parameters on which sample size is based (apart from treatment differences) should be evaluated as part of interim monitoring of the study by the investigators; and 5. In the long run, it pays to be conservative in estimating sample size. The general formula for sample size for 2 groups with 1:1 allocation can be written as: N per group = 2 X Variability X [constant ( α , β )] 2 ____________________________________ Delta 2 X = “times” α = Type I error or significance level - probability that the trial will find two treatments that are equally effective "significantly" different from one another....
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This note was uploaded on 11/21/2011 for the course PUBH 7420 taught by Professor Ph7420 during the Spring '07 term at Minnesota.
- Spring '07