Multiple comparisons: Tukey

Source: R/HSD.test.R

It makes multiple comparisons of treatments by means of Tukey. The level by alpha default is 0.05.

HSD.test(
  y,
  trt,
  DFerror,
  MSerror,
  alpha = 0.05,
  group = TRUE,
  main = NULL,
  unbalanced = FALSE,
  console = FALSE
)

Arguments

y

model(aov or lm) or answer of the experimental unit
trt

Constant( only y=model) or vector treatment applied to each experimental unit
DFerror

Degree free
MSerror

Mean Square Error
alpha

Significant level
group

TRUE or FALSE
main

Title
unbalanced

TRUE or FALSE. not equal replication
console

logical, print output

Value

statistics

Statistics of the model

parameters

Design parameters

means

Statistical summary of the study variable

comparison

Comparison between treatments

groups

Formation of treatment groups

Details

It is necessary first makes a analysis of variance.

if y = model, then to apply the instruction:
HSD.test (model, "trt", alpha = 0.05, group = TRUE, main = NULL, unbalanced=FALSE, console=FALSE)
where the model class is aov or lm.

References

1. Principles and procedures of statistics a biometrical approach Steel & Torry & Dickey. Third Edition 1997
2. Multiple comparisons theory and methods. Departament of statistics the Ohio State University. USA, 1996. Jason C. Hsu. Chapman Hall/CRC.

See also

BIB.test, DAU.test, duncan.test, durbin.test, friedman, kruskal, LSD.test, Median.test, PBIB.test, REGW.test, scheffe.test, SNK.test, waerden.test, waller.test, plot.group

Examples


library(agricolae)
data(sweetpotato)
model<-aov(yield~virus, data=sweetpotato)
out <- HSD.test(model,"virus", group=TRUE,console=TRUE,
main="Yield of sweetpotato\nDealt with different virus")
#> 
#> Study: Yield of sweetpotato
#> Dealt with different virus
#> 
#> HSD Test for yield 
#> 
#> Mean Square Error:  22.48917 
#> 
#> 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
#> 
#> Alpha: 0.05 ; DF Error: 8 
#> Critical Value of Studentized Range: 4.52881 
#> 
#> Minimun Significant Difference: 12.39967 
#> 
#> Treatments with the same letter are not significantly different.
#> 
#>       yield groups
#> oo 36.90000      a
#> ff 36.33333     ab
#> cc 24.40000     bc
#> fc 12.86667      c
#stargraph
# Variation range: max and min
plot(out)
#> Warning: NAs introduced by coercion
#endgraph
out<-HSD.test(model,"virus", group=FALSE)
print(out$comparison)
#>          difference pvalue signif.         LCL         UCL
#> cc - fc  11.5333333 0.0686       .  -0.8663365  23.9330031
#> cc - ff -11.9333333 0.0592       . -24.3330031   0.4663365
#> cc - oo -12.5000000 0.0482       * -24.8996698  -0.1003302
#> fc - ff -23.4666667 0.0014      ** -35.8663365 -11.0669969
#> fc - oo -24.0333333 0.0012      ** -36.4330031 -11.6336635
#> ff - oo  -0.5666667 0.9988         -12.9663365  11.8330031
# Old version HSD.test()
df<-df.residual(model)
MSerror<-deviance(model)/df
with(sweetpotato,HSD.test(yield,virus,df,MSerror, group=TRUE,console=TRUE,
main="Yield of sweetpotato. Dealt with different virus"))
#> 
#> Study: Yield of sweetpotato. Dealt with different virus
#> 
#> HSD Test for yield 
#> 
#> Mean Square Error:  22.48917 
#> 
#> 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
#> 
#> Alpha: 0.05 ; DF Error: 8 
#> Critical Value of Studentized Range: 4.52881 
#> 
#> Minimun Significant Difference: 12.39967 
#> 
#> Treatments with the same letter are not significantly different.
#> 
#>       yield groups
#> oo 36.90000      a
#> ff 36.33333     ab
#> cc 24.40000     bc
#> fc 12.86667      c