Statistical significance and statistical power in hypothesis testing
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چکیده
منابع مشابه
Statistical significance and statistical power in hypothesis testing.
Experimental design requires estimation of the sample size required to produce a meaningful conclusion. Often, experimental results are performed with sample sizes which are inappropriate to adequately support the conclusions made. In this paper, two factors which are involved in sample size estimation are detailed--namely type I (alpha) and type II (beta) error. Type I error can be considered ...
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In comparing or assessing methods of treatment it is vital that the appropriate number of patients is selected in order to ensure that the conclusions drawn are statistically viable. This annotation describes the relevance of a statistical power analysis in the context of hypothesis testing to the determination of the optimal sample size of a study. The power of the test indicates how likely it...
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1 From the Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, Mass (K.H.Z., J.R.F., S.G.S., C.M.C.T.); and Department of Health Care Policy, Harvard Medical School, 180 Longwood Ave, Boston, MA 02115 (K.H.Z.). Received September 10, 2001; revision requested November 8; revision received December 12; accepted December 19. Supported in part by Public Health Ser...
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A statistically significant research finding should not be defined as a P-value of 0.05 or less, because this definition does not take into account study power. Statistical significance was originally defined by Fisher RA as a P-value of 0.05 or less. According to Fisher, any finding that is likely to occur by random variation no more than 1 in 20 times is considered significant. Neyman J and P...
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ژورنال
عنوان ژورنال: Journal of Orthopaedic Research
سال: 1990
ISSN: 0736-0266,1554-527X
DOI: 10.1002/jor.1100080221