Multiple range tests for all pairwise comparisons, to obtain a confident inequalities multiple range tests.
REGW.test( y, trt, DFerror, MSerror, alpha = 0.05, group = TRUE, main = NULL, console = FALSE )
| 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 |
| console | logical, print output |
Statistics of the model
Design parameters
Critical Range Table
Statistical summary of the study variable
Comparison between treatments
Formation of treatment groups
It is necessary first makes a analysis of variance.
if y = model, then to apply the instruction:
REGW.test (model, "trt",
alpha = 0.05, group = TRUE, main = NULL, console = FALSE)
where the model
class is aov or lm.
Multiple comparisons theory and methods. Departament of statistics the Ohio State University. USA, 1996. Jason C. Hsu. Chapman Hall/CRC
BIB.test, DAU.test,
duncan.test, durbin.test,
friedman, HSD.test, kruskal,
LSD.test, Median.test, PBIB.test,
scheffe.test, SNK.test,
waerden.test, waller.test,
plot.group
library(agricolae) data(sweetpotato) model<-aov(yield~virus,data=sweetpotato) out<- REGW.test(model,"virus", main="Yield of sweetpotato. Dealt with different virus") print(out)#> $statistics #> MSerror Df Mean CV #> 22.48917 8 27.625 17.1666 #> #> $parameters #> test name.t ntr alpha #> REGW virus 4 0.05 #> #> $regw #> Table CriticalRange #> 2 3.879582 10.62212 #> 3 4.041036 11.06417 #> 4 4.528810 12.39967 #> #> $means #> yield std r Min Max Q25 Q50 Q75 #> cc 24.40000 3.609709 3 21.7 28.5 22.35 23.0 25.75 #> fc 12.86667 2.159475 3 10.6 14.9 11.85 13.1 14.00 #> ff 36.33333 7.333030 3 28.0 41.8 33.60 39.2 40.50 #> oo 36.90000 4.300000 3 32.1 40.4 35.15 38.2 39.30 #> #> $comparison #> NULL #> #> $groups #> yield groups #> oo 36.90000 a #> ff 36.33333 a #> cc 24.40000 b #> fc 12.86667 c #> #> attr(,"class") #> [1] "group"REGW.test(model,"virus",alpha=0.05,console=TRUE,group=FALSE)#> #> Study: model ~ "virus" #> #> Ryan, Einot and Gabriel and Welsch multiple range 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 #> #> Comparison between treatments means #> #> difference pvalue signif. LCL UCL #> cc - fc 11.5333333 0.0350 * 0.9112173 22.1554494 #> cc - ff -11.9333333 0.0360 * -22.9975029 -0.8691637 #> cc - oo -12.5000000 0.0482 * -24.8996698 -0.1003302 #> fc - ff -23.4666667 0.0006 *** -34.0887827 -12.8445506 #> fc - oo -24.0333333 0.0007 *** -35.0975029 -12.9691637 #> ff - oo -0.5666667 0.9873 -11.1887827 10.0554494