Message-ID: <42F29071.1000107@fe.up.pt>
Date: 2005-08-04T22:02:25Z
From: Peter Ho
Subject: p-values
HI R-users,
I am trying to repeat an example from Rayner and Best "A contingency
table approach to nonparametric testing (Chapter 7, Ice cream example).
In their book they calculate Durbin's statistic, D1, a dispersion
statistics, D2, and a residual. P-values for each statistic is
calculated from a chi-square distribution and also Monte Carlo p-values.
I have found similar p-values based on the chi-square distribution by
using:
> pchisq(12, df= 6, lower.tail=F)
[1] 0.0619688
> pchisq(5.1, df= 6, lower.tail=F)
[1] 0.5310529
Is there a way to calculate the equivalent Monte Carlo p-values?
The values were 0.02 and 0.138 respectively.
The use of the approximate chi-square probabilities for Durbin's test
are considered not good enough according to Van der Laan (The American
Statistician 1988,42,165-166).
Peter
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ESTG-IPVC