Singh G
Department of Basic Principles, Institute of Medical Sciences, Banaras Hindu University, Varanasi-221 005, India.
J Postgrad Med. 2006 Apr-Jun;52(2):148-50.
Medical research literature until recently, exhibited substantial dominance of the Fisher's significance test approach of statistical inference concentrating more on probability of type I error over Neyman-Pearson's hypothesis test considering both probability of type I and II error. Fisher's approach dichotomises results into significant or not significant results with a P value. The Neyman-Pearson's approach talks of acceptance or rejection of null hypothesis. Based on the same theory these two approaches deal with same objective and conclude in their own way. The advancement in computing techniques and availability of statistical software have resulted in increasing application of power calculations in medical research and thereby reporting the result of significance tests in the light of power of the test also. Significance test approach, when it incorporates power analysis contains the essence of hypothesis test approach. It may be safely argued that rising application of power analysis in medical research may have initiated a shift from Fisher's significance test to Neyman-Pearson's hypothesis test procedure.
直到最近，医学研究文献在统计推断方面都显著倾向于费希尔显著性检验方法，该方法更关注I型错误的概率，而不是同时考虑I型和II型错误概率的奈曼 - 皮尔逊假设检验。费希尔的方法通过P值将结果二分法为显著或不显著的结果。奈曼 - 皮尔逊的方法则讨论原假设的接受或拒绝。基于相同的理论，这两种方法处理相同的目标并以各自的方式得出结论。计算技术的进步和统计软件的可用性导致了功效计算在医学研究中的应用增加，从而也根据检验功效来报告显著性检验的结果。当显著性检验方法纳入功效分析时，它包含了假设检验方法的本质。可以有把握地说，功效分析在医学研究中的应用不断增加，可能已经引发了从费希尔显著性检验到奈曼 - 皮尔逊假设检验程序的转变。
