Read full paper at: http://www.scirp.org/journal/PaperInformation.aspx?PaperID=54078#.VO1rTyzQrzE Author(s) L. Jiang , A. Wong Affiliation(s) Department of Mathematics and Statistics, York University, Toronto, Canada . ABSTRACT Fisher [1] proposed a simple method to combine p -values from independent investigations without using detailed information of the original data. In recent years, likelihood-based asymptotic methods have been developed to produce highly accurate p -values. These likelihood-based methods generally required the likelihood function and the standardized maximum likelihood estimates departure calculated in the canonical parameter scale. In this paper, a method is proposed to obtain a p -value by combining the likelihood functions and the standardized maximum likelihood estimates departure of independent investigations for testing a scalar parameter of interest. Examples are presented to illustrate the application ...
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