Message-ID: <Pine.A41.4.44.0304230743030.13728-100000@homer40.u.washington.edu>
Date: 2003-04-23T14:44:04Z
From: Thomas Lumley
Subject: fisher exact vs. simulated chi-square
In-Reply-To: <0d3f01c3098a$de191b30$6501a8c0@HydePark>
On Wed, 23 Apr 2003, Bob Porter wrote:
> The Chi-Square test is based upon the assumption that the sample is large enough
> to allow approximation of a (nearly symetric) binomial by a normal distribution.
> (Chi Sqare is z^2). When expected (NOT observed) cells are too small, that
> suggests a very asymetric binomial and, consequently a poor fit for the
> assumption. The exact test calculates the exact probability of the observed
> values, or more extreme ones, given the assumed probabilities generating the
> expected values. As someone else noted, exact is exact, Chi-square is not
> (unless, of course, assumptions are exactly met.)
This is true but not the issue. The question was about the difference
between the Fisher p.value and a Monte Carlo estimate of the exact p value
for the chisquared statisic.
-thomas