Sign up for email alert when new content gets added: Sign up
Guolong Zhao, Huiyu Yang, Junxia Yang, Liufeng Zhang, Xiaoang Yang
Henan Institute of Medical Sciences, China
ScientificTracks Abstracts: Health Pol
Fisher exact test is one of most popularly used methods in modern data analyses. However, it is conservative because of discreteness. The mid-p method may reduce the conservativeness but it is defined by the factor 1/2, an extra term beyond data. This paper considers an adjustment defined by a data-based factor. The adjusted test is compared with other ten tests. Special attention is given to the comparison between the data-based factor and the factor 1/2. The standardized version of the adjusted test is asymptotically standard normal. The adjustment reduces the conservativeness, as evidenced by increasing test size and power and decreasing p-values. The adjusted test holds such properties as the significance level under control of nominal α, the same modification in the left- and right-sided p-values, and the proportional reduction from Fisher test, which the mid-p method lacks. The mid-p method is more powerful than the adjusted test but the increment of power comes from the factor 1/2 and is not controlled by α. The unconditional tests are also more powerful but the power comes partly from the unobserved samples. The proper choice of an adjustment is based largely upon a consideration of both the power of test and the origin of power so that the adjusted test is an option in data analyses. It is easy to implement for 2×2 and r×c contingency tables. Two real examples are given for analyzing 2×2 tables and another example for r×c tables. MSC 2010 subject classifications: Primary 62H15; secondary 62H17 Key words: adjustment; Barnard exact test; conservativeness; contingency table; Fisher exact test; mid-p method. Recent publications 1. Fisher RA (1922) On the interpretation of χ2 from contingency tables, and the calculation of P. Journal of the Royal Statistical Society 85: 87-94. 2. Fisher RA (1970) Statistical Methods for Research Workers (14th Edn) New York: Hafner, USA. 3. Agresti A (1992) A survey of exact inference for contingency tables. Statistical Science 7 131-53.
Guolong Zhao, MD, AUF., a Chinese physician at Henan Institute of Medical Sciences, Zhengzhou University, 40 University Road, Zhengzhou, Henan 450052, China, was born on January 16, 1942, known for his work on survival analysis, cancer epidemiology, and clinical evaluation of drugs. In 1998 he received the 2nd prize of sciences (98000) conferred by the Henan Commission of Science and Technology and the 1st prize of medical sciences (9602) conferred by the Department of Public Health of Henan. There are 93 papers published such as Zhao G. Tests of non-null hypothesis on proportions for stratified data. Statistics in Medicine, 2008; 27(9): 1429-1446. (http://dx.doi.org/10.1002/sim.3023), Zhao G. A test of non-null hypothesis for linear trends in proportions. Communications in Statistics - Theory and Methods 2015; 44(8): 1621-1639.
+447915641605
