Sample Size Estimation: A Glimpse beyond Simple Formulas

Radiology

Volumn 230, Issue 3, 2004, Pages 606-612

  Eng, John ^a  

^a JOHNS HOPKINS UNIVERSITY   (United States)

Author keywords

Radiology and radiologists, research; Receiver operating characteristic (ROC) curve; Statistical analysis

Indexed keywords

CALCULATION; ETHICS; MONTE CARLO METHOD; PRIORITY JOURNAL; RECEIVER OPERATING CHARACTERISTIC; REVIEW; SAMPLE SIZE; SIMULATION; STATISTICS;

CLINICAL TRIALS; DIAGNOSTIC IMAGING; ETHICS, RESEARCH; HUMANS; MATHEMATICAL COMPUTING; MODELS, STATISTICAL; REPRODUCIBILITY OF RESULTS; ROC CURVE; SAMPLE SIZE;

EID: 1342330117     PISSN: 00338419     EISSN: None     Source Type: Journal    
DOI: 10.1148/radiol.2303030297     Document Type: Review

References (21)

1. Eng J. Sample size estimation: how many individuals should be studied? Radiology 2003; 227:309-313.
2. Eng J, Siegelman SS. Improving radiology research methods: what is being asked and who is being studied? Radiology 1997; 205:651-655.
3. Newell DJ. Type II errors and ethics (letter). BMJ 1978; 4:1789.
4. Halpern SD, Karlawish JHT, Berlin JA. The continuing unethical conduct of under-powered clinical trials. JAMA 2002; 288: 358-362.
5. Rosner B. Fundamentals of biostatistics. 5th ed. Pacific Grove, Calif: Duxbury, 2000; 308.
6. Lenth RV. Some practical guidelines for effective sample size determination. Am Stat 2001; 55:187-193.
7. Hoenig JM, Heisey DM. The abuse of power: the pervasive fallacy of power calculations for data analysis. Am Stat 2001; 55:19-24.
8. Thomas L. Retrospective power analysis. Conserv Biol 1997; 11:276-280.
9. Detsky AS, Sackett DL. When was a "negative" clinical trial big enough? How many patients you need depends on what you found. Arch Intern Med 1985; 145: 709-712.
10. Castelloe JM. Sample size computations and power analysis with the SAS system. Proceedings of the 25th Annual SAS Users Group International Conference, April 9-12, 2000, Indianapolis, Ind. Cary, NC: SAS Institute, 2000.
11. Feiveson AH. Power by simulation. Stata J 2002; 2:107-124.
12. Obuchowski NA. Multireader receiver operating characteristic studies: a comparison of study designs. Acad Radiol 1995; 2:709-716.
13. Zhou XH, Obuchowski NA, McClish DK. Statistical methods in diagnostic medicine. New York, NY: Wiley, 2002; 298-304.
14. Obuchowski NA. Sample size tables for receiver operating characteristic studies. AJR Am J Roentgenol 2000; 175:603-608.
15. Dorfman DD, Berbaum KS, Metz CE. Receiver operating characteristic rating analysis: generalization to the population of readers and patients with the jackknife method. Invest Radiol 1992; 27:723-731.
16. Roe CA, Metz CE. Dorfman-Berbaum-Metz method for statistical analysis of multireader, multimodality receiver operating characteristic data: validation with computer simulation. Acad Radiol 1997; 4:298-303.
17. Dorfman DD, Berbaum KS, Lenth RV, Chen YF, Donaghy BA. Monte Carlo validation of a multireader method for receiver operating characteristic discrete rating data: factorial experimental design. Acad Radiol 1998; 5:591-602.
18. Abramowitz M, Stegun IA. Handbook of mathematical functions with formulas, graphs, and mathematical tables. Washington, DC: U.S. Department of Commerce, National Bureau of Standards, 1964. Applied Mathematics Series No. 55.
19. Feinstein AR. Principles of medical statistics. Boca Raton, Fla: Chapman & Hall, 2002; 115-116.
20. Lenth RV. Java applets for power and sample size. Available at: www.stat.uiowa.edu/~rlenth/Power/index.html. Accessed January 5, 2004.
21. Snedecor GW, Cochran WG. Statistical methods. 8th ed. Ames, Iowa: Iowa State University Press, 1989; 469.