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http://www.scirp.org/journal/PaperInformation.aspx?PaperID=54078#.VO1rTyzQrzE
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 of the proposed method and
simulation studies are performed to compare the accuracy of the proposed
method with Fisher’s method.
KEYWORDS
Canonical Parameter, Fisher’s Expected Information, Modified Signed Log-Likelihood Ratio Statistic, Standardized Maximum Likelihood Estimate Departure
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References
Jiang, L. and Wong, A. (2015) Combining Likelihood Information from Independent Investigations. Open Journal of Statistics, 5, 51-59. doi: 10.4236/ojs.2015.51007.
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