## This uses the same data as the HH Section 12.13 rhizobium example.
rhiz.clover <- read.table(hh("datasets/rhiz3-clover.dat"), header=TRUE)
rhiz.clover$comb <- factor(rhiz.clover$comb,
labels=c("clover","clover+alfalfa"))
position(rhiz.clover$comb) <- c(2,5)
rhiz.clover$strain <-
factor(rhiz.clover$strain,
labels=c('3DOk1','3DOk5','3DOk4','3DOk7','3DOk13','k.comp'))
rhiz.clover$Npg <- rhiz.clover$nitro / rhiz.clover$weight
## interaction plot, no se
intxplot(Npg ~ strain, groups=comb, data=rhiz.clover)
## interaction plot, individual se for each treatment combination
intxplot(Npg ~ strain, groups=comb, data=rhiz.clover, se=TRUE)
## Rescaled to allow the CI bars to stay within the plot region
intxplot(Npg ~ strain, groups=comb, data=rhiz.clover, se=TRUE,
ylim=range(rhiz.clover$Npg))
## interaction plot, common se based on ANOVA table
intxplot(Npg ~ strain, groups=comb, data=rhiz.clover,
se=sqrt(sum((nobs-1)*sd^2)/(sum(nobs-1)))/sqrt(5))
## Rescaled to allow the CI bars to stay within the plot region
intxplot(Npg ~ strain, groups=comb, data=rhiz.clover,
se=sqrt(sum((nobs-1)*sd^2)/(sum(nobs-1)))/sqrt(5),
ylim=range(rhiz.clover$Npg))
## change distance between endpoints
intxplot(Npg ~ strain, groups=comb, data=rhiz.clover,
se=TRUE, offset.scale=20)
## When data includes the nobs and sd variables, data.is.summary=TRUE is needed.
intxplot(Npg ~ strain, groups=comb,
se=sqrt(sum((nobs-1)*sd^2)/(sum(nobs-1)))/sqrt(5),
data=sufficient(rhiz.clover, y="Npg", c("strain","comb")),
data.is.summary=TRUE,
ylim=range(rhiz.clover$Npg))
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