Clinical trials are often costly, and time consuming. The ability to get new products into the market early is critical to the success of pharmaceutical and medical device companies. Most practitioners use Fisher's exact tests to determine the required sample size for testing efficacy rates. We shall argue that when the sample size is not too small, normal approximation tests should be used instead of Fisher's exact tests. Several different sets of hypotheses and their corresponding formulas to compute sample size for clinical trial based upon normal approximation test are given.
| Published in | Biomedical Statistics and Informatics (Volume 2, Issue 3) |
| DOI | 10.11648/j.bsi.20170203.12 |
| Page(s) | 103-106 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2017. Published by Science Publishing Group |
Fisher’s Exact Test, Normal Approximation Test, Clinical Trial, Clinical Significance, Efficacy Rate
| [1] | Casella, G. and Berger, R. L., “Statistical Inference” 2nd ed. Pacific Grove, CA: Duxbury. 2002. |
| [2] | Pocock, S. J., “Clinical Trials: A Practical Approach” New York, NY: John Wiley & Sons. 1983. |
| [3] | Rohatgi, V. K. and Saleh, A. K. M. E., “An Introduction to Probability and Statistics” 3rd ed. New York, NY: John Wiley & Sons. 2015. |
| [4] | Hogg, R. V. and Tanis, E. A., “Probability and Statistical Inference” Upper Saddle River, NJ: Pearson. 2010. |
| [5] | D’Agostino, R. B., Chases, W., and Belanger, A., “The Appropriateness of Some Common Procedures for Testing the Equality of Two Independent Binomial Populations,” The American Statistician, Vol. 42, No. 3, 198-202. 1988. |
| [6] | Upton, U. J. G., “A Comparison of Alternative Tests for the 2x2 Comparative Trial, “Journal of the Royal Statistical Society, Ser. A, 145, 86-105. 1982. |
| [7] | Berkson, J., "In Dispraise of the Exact Test," Journal of Statistical Planning and Inference, 2, 27-42. 1978. |
| [8] | Conover, W. J., "Some Reasons for Not Using the Yates Continuing Correction on 2 x 2 Contingency Tables, " Journal of the American Statistical Association, 69, 374-376. 1974. |
| [9] | Grizzle, J. E., "Continuity Correction in the X2 Test for 2 x 2 Tables," The American Statistician, 21, 28-32. 1967. |
| [10] | Kempthorne, O., "In Dispraise of the Exact Test: Reactions," Journal of Statistical Planning and Inference, 3, 199-213. 1979. |
| [11] | DeGroot, M. H. and Schervish, M. J. “Probability and Statistics” 3rd ed. Boston, MA: Addison-Wesley, 2002. |
| [12] | Fienberg, S. E., “The Analysis of Cross-Classified Categorical Data” 2nd ed. Cambridge, MA: MIT Press, 1980. |
| [13] | Bishop, Y. M. M., Fienberg, S. E. and Holland, P. W. “Discrete Multivariate Analysis: Theory and Practice” Cambridge, MA: MIT Press, 1975. |
APA Style
Thomas Jyh-Ming Jiang. (2017). Optimal Sample Size Determination for Medium or Large Clinical Study. Biomedical Statistics and Informatics, 2(3), 103-106. https://doi.org/10.11648/j.bsi.20170203.12
ACS Style
Thomas Jyh-Ming Jiang. Optimal Sample Size Determination for Medium or Large Clinical Study. Biomed. Stat. Inform. 2017, 2(3), 103-106. doi: 10.11648/j.bsi.20170203.12
Share This Article
Twitter
Linked In
Facebook
Copy
Download@article{10.11648/j.bsi.20170203.12,
author = {Thomas Jyh-Ming Jiang},
title = {Optimal Sample Size Determination for Medium or Large Clinical Study},
journal = {Biomedical Statistics and Informatics},
volume = {2},
number = {3},
pages = {103-106},
doi = {10.11648/j.bsi.20170203.12},
url = {https://doi.org/10.11648/j.bsi.20170203.12},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.bsi.20170203.12},
abstract = {Clinical trials are often costly, and time consuming. The ability to get new products into the market early is critical to the success of pharmaceutical and medical device companies. Most practitioners use Fisher's exact tests to determine the required sample size for testing efficacy rates. We shall argue that when the sample size is not too small, normal approximation tests should be used instead of Fisher's exact tests. Several different sets of hypotheses and their corresponding formulas to compute sample size for clinical trial based upon normal approximation test are given.},
year = {2017}
}
TY - JOUR T1 - Optimal Sample Size Determination for Medium or Large Clinical Study AU - Thomas Jyh-Ming Jiang Y1 - 2017/03/29 PY - 2017 N1 - https://doi.org/10.11648/j.bsi.20170203.12 DO - 10.11648/j.bsi.20170203.12 T2 - Biomedical Statistics and Informatics JF - Biomedical Statistics and Informatics JO - Biomedical Statistics and Informatics SP - 103 EP - 106 PB - Science Publishing Group SN - 2578-8728 UR - https://doi.org/10.11648/j.bsi.20170203.12 AB - Clinical trials are often costly, and time consuming. The ability to get new products into the market early is critical to the success of pharmaceutical and medical device companies. Most practitioners use Fisher's exact tests to determine the required sample size for testing efficacy rates. We shall argue that when the sample size is not too small, normal approximation tests should be used instead of Fisher's exact tests. Several different sets of hypotheses and their corresponding formulas to compute sample size for clinical trial based upon normal approximation test are given. VL - 2 IS - 3 ER -
Email: