[R] Fisher's LSD multiple comparisons in a two-way ANOVA
Jinsong Zhao
jszhao at yeah.net
Fri Apr 6 11:01:13 CEST 2012
On 2012-04-05 10:49, Richard M. Heiberger wrote:
> Here is your example. The table you displayed in gigawiz ignored the
> two-way factor structure
> and interpreted the data as a single factor with 6 levels. I created
> the interaction of
> a and b to get that behavior.
> ## your example, with data stored in a data.frame
> tmp <- data.frame(x=c(76, 84, 78, 80, 82, 70, 62, 72,
> 71, 69, 72, 74, 66, 74, 68, 66,
> 69, 72, 72, 78, 74, 71, 73, 67,
> 86, 67, 72, 85, 87, 74, 83, 86,
> 66, 68, 70, 76, 78, 76, 69, 74,
> 72, 72, 76, 69, 69, 82, 79, 81),
> a=factor(rep(c("A1", "A2"), each = 24)),
> b=factor(rep(c("B1", "B2", "B3"), each=8, times=2)))
> x.aov <- aov(x ~ a*b, data=tmp)
> summary(x.aov)
> ## your request
> require(multcomp)
> tmp$ab <- with(tmp, interaction(a, b))
> xi.aov <- aov(x ~ ab, data=tmp)
> summary(xi.aov)
> xi.glht <- glht(xi.aov, linfct=mcp(ab="Tukey"))
> confint(xi.glht)
>
> ## graphs
> ## boxplots
> require(lattice)
> bwplot(x ~ ab, data=tmp)
> ## interaction plot
> ## install.packages("HH") ## if you don't have HH yet
> require(HH)
> interaction2wt(x ~ a*b, data=tmp)
>
Thank you very much for the demonstration.
There is still a small difference between the results of glht() and the
the table displayed in gigawiz. I try my best to figure out, but fail...
By the way, I have a similar question. I built a ANOVA model:
activity ~ pH * I * f
Df Sum Sq Mean Sq F value Pr(>F)
pH 1 1330 1330 59.752 2.15e-10 ***
I 1 137 137 6.131 0.0163 *
f 6 23054 3842 172.585 < 2e-16 ***
pH:I 1 152 152 6.809 0.0116 *
pH:f 6 274 46 2.049 0.0741 .
I:f 6 5015 836 37.544 < 2e-16 ***
pH:I:f 6 849 142 6.356 3.82e-05 ***
Residuals 56 1247 22
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.
Now, how can I do a multi-comparison on `pH:I'?
Do I need to do separate ANOVA for each `pH' or `I', just as that in
demo("MMC.WoodEnergy", "HH")? And then do multi-comparison on `I' or
`pH' in each separate ANOVA?
Thanks again.
Regards,
Jinsong
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