Plotting the standard error or standard deviance of a multiple comparison of means

It plots bars of the averages of treatments and standard error or standard deviance. It uses the objects generated by a procedure of comparison like LSD, HSD, Kruskal and Waller-Duncan.

x: data frame formed by 5 columns: name of the bars, height, level out: LSD.test, HSD, waller.test, scheffe.test, duncan.test, SNK.test, friedman, kruskal, waerden.test and Median.test.

bar.err(
  x,
  variation = c("SE", "SD", "range", "IQR"),
  horiz = FALSE,
  bar = TRUE,
  ...
)

# S3 method for default
bar.err(
  x,
  variation = c("SE", "SD", "range", "IQR"),
  horiz = FALSE,
  bar = TRUE,
  ...
)

Arguments

x	object means of the comparisons the LSD.test, HSD.test,...,etc
variation	SE=standard error, range=Max-Min or IQR=interquartil range
horiz	Horizontal or vertical bars
bar	paint bar
...	Parameters of the function barplot()

Value

A list with numeric vectors giving the coordinates of all the bar midpoints drawn.

x eje-1 coordinate

height eje-2 coordinate by group

See also

LSD.test, HSD.test, waller.test, kruskal, bar.group

Examples

library(agricolae)
data(sweetpotato)
model<-aov(yield~virus,data=sweetpotato)
out <- waller.test(model,"virus", console=TRUE,
main="Yield of sweetpotato\ndealt with different virus")
#> 
#> Study: Yield of sweetpotato
#> dealt with different virus 
#> 
#> Waller-Duncan K-ratio t Test for yield 
#> 
#> This test minimizes the Bayes risk under additive loss and certain other assumptions
#>                             ......
#> K ratio                  100.00000
#> Error Degrees of Freedom   8.00000
#> Error Mean Square         22.48917
#> F value                   17.34478
#> Critical Value of Waller   2.23600
#> 
#> virus,  means
#> 
#>       yield      std r  Min  Max
#> cc 24.40000 3.609709 3 21.7 28.5
#> fc 12.86667 2.159475 3 10.6 14.9
#> ff 36.33333 7.333030 3 28.0 41.8
#> oo 36.90000 4.300000 3 32.1 40.4
#> 
#> Minimum Significant Difference 8.657906
#> Treatments with the same letter are not significantly different.
#> 
#>       yield groups
#> oo 36.90000      a
#> ff 36.33333      a
#> cc 24.40000      b
#> fc 12.86667      c
oldpar<-par(mfrow=c(2,2),cex=1)
bar.err(out$means,variation="range",horiz=TRUE,xlim=c(0,45),angle=125,density=6,
 main="range")
bar.err(out$means,variation="SD",ylim=c(0,45),col=colors()[30],
 main="Standard deviation",density=8)
bar.err(out$means,variation="SE",horiz=TRUE,xlim=c(0,45),density=8,
 col="brown",main="Standard error")
bar.err(out$means,variation="range",ylim=c(0,45),bar=FALSE,col="green",
 main="range")
par(mfrow=c(1,2),cex=1)
bar.err(out$means,variation="range",ylim=c(0,45),bar=FALSE,col=0)
abline(h=0)
# horiz = TRUE
bar.err(out$means,variation="SE",horiz=TRUE,xlim=c(0,45),bar=FALSE,col=0)
#startgraph
par(oldpar)
#endgraph