scheffe.test {agricolae} R Documentation

Multiple comparisons, scheffe

Description

Scheffe 1959, method is very general in that all possible contrasts can be tested for significance and confidence intervals can be constructed for the corresponding linear. The test is conservative.

Usage

scheffe.test(y, trt, DFerror, MSerror, Fc, alpha = 0.05, group=TRUE, main = NULL,
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 Degrees of freedom MSerror Mean Square Error Fc F Value alpha Significant level group TRUE or FALSE main Title console logical, print output

Details

It is necessary first makes a analysis of variance.

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

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

Author(s)

Felipe de Mendiburu

References

Robert O. Kuehl. 2nd ed. Design of experiments. Duxbury, copyright 2000.
Steel, R.; Torri,J; Dickey, D.(1997) Principles and Procedures of Statistics A Biometrical Approach. pp189

See Also

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

Examples

library(agricolae)
data(sweetpotato)
model<-aov(yield~virus, data=sweetpotato)
comparison <- scheffe.test(model,"virus", group=TRUE,console=TRUE,
main="Yield of sweetpotato\nDealt with different virus")
# Old version scheffe.test()
df<-df.residual(model)
MSerror<-deviance(model)/df
Fc<-anova(model)["virus",4]
out <- with(sweetpotato,scheffe.test(yield, virus, df, MSerror, Fc))
print(out)


[Package agricolae version 1.3-7 Index]