scheffe.test {agricolae}

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)