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0.0377
2003 Jul 15
1
Why two chisq.test p values differ when the contingency table is transposed?
I'm using R1.7.0 runing with Win XP. Thanks,
...Tao
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>x
[,1] [,2]
[1,] 149 151
[2,] 1 8
>t(x)
[,1] [,2]
[1,] 149 1
[2,] 151 8
>chisq.test(x, simulate.p.value=T, B=100000)
Pearson's Chi-squared test with simulated p-value (based on 1e+05
replicates)
data: x
X-squared = 5.2001, df =
2003 Jul 15
0
Why two chisq.test p values differ when the contingency
Hi Tao:
The P-values for 2x2 table are generated based on a random (discrete
uniform distribution) sampling of all possible 2x2 tables, conditioning
on the observed margin totals. If one of the cells is extremely small,
as in your case, you get a big difference in P-values. Suppose, you
changed the cell with value 1 to, say, 5 or 6, then the two P-values
are nearly the same. However, I
2008 Jun 03
1
Model simplification using anova()
Hello all,
I've become confused by the output produced by a call to
anova(model1,model2). First a brief background. My model used to predict
final tree height is summarised here:
Df Sum Sq Mean Sq F value Pr(>F)
Treatment 2 748.35 374.17 21.3096 7.123e-06 ***
HeightInitial 1 0.31 0.31 0.0178 0.89519