:I’m still waiting to hear which literature says that “Monte Carlo resampling” is “more accurate than the chi-squared test”. The page mentioned above [http://faculty.vassar.edu/lowry/chi_beta.html] is a discussion of why statisticians “fail to reject the null” rather than “accepting the null” when the p-value is above 0.05 or so. The page says nothing about superiority of Monte Carlo methods. Why were alternate hypothesis distributions mentioned? Only the null hypothesis distribution is used to calculate a p-value. Yates’s correction is for 2x2 contingency tables [http://en.wikipedia.org/wiki/Yates%27_correction_for_continuity]. It doesn’t apply in this case. Finally, what the heck do “covariance structure analysis” and “allele frequencies at a highly polymorphic locus” have to do with this problem? [[User:SJohnson|SJohnson]] 16:38, 5 March 2009 (EST)
:Regarding the "Fisher z-transformation p-value" from the paper, garbage in garbage out. If the p-values were bad to begin with, then why would a combination of them be meaningful? [[User:SJohnson|SJohnson]] 10:49, 9 March 2009 (EDT)
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