| waller.test {agricolae} | R Documentation |
The Waller-Duncan k-ratio t test is performed on all main effect means in the MEANS statement. See the K-RATIO option for information on controlling details of the test.
waller.test(y, trt, DFerror, MSerror, Fc, K = 100, 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 unit |
DFerror |
Degrees of freedom |
MSerror |
Mean Square Error |
Fc |
F Value |
K |
K-RATIO |
group |
TRUE or FALSE |
main |
Title |
console |
logical, print output |
It is necessary first makes a analysis of variance.
K-RATIO (K): value specifies the Type 1/Type 2 error seriousness ratio for the Waller-Duncan test. Reasonable values for KRATIO are 50, 100, and 500, which roughly correspond for the two-level case to ALPHA levels of 0.1, 0.05, and 0.01. By default, the procedure uses the default value of 100.
statistics |
Statistics of the model |
parameters |
Design parameters |
means |
Statistical summary of the study variable |
comparison |
Comparison between treatments |
groups |
Formation of treatment groups |
Felipe de Mendiburu
Waller, R. A. and Duncan, D. B. (1969). A Bayes Rule for the Symmetric Multiple Comparison Problem, Journal of the American Statistical Association 64, pages 1484-1504.
Waller, R. A. and Kemp, K. E. (1976) Computations of Bayesian t-Values for Multiple Comparisons, Journal of Statistical Computation and Simulation, 75, pages 169-172.
Steel & Torry & Dickey. Third Edition 1997 Principles and procedures of statistics a biometrical approach
BIB.test, DAU.test, duncan.test,
durbin.test, friedman, HSD.test,
kruskal, LSD.test, Median.test,
PBIB.test, REGW.test, scheffe.test,
SNK.test, waerden.test, plot.group
library(agricolae) data(sweetpotato) model<-aov(yield~virus, data=sweetpotato) out <- waller.test(model,"virus", group=TRUE) #startgraph par(mfrow=c(2,2)) # variation: SE is error standard # variation: range is Max - Min bar.err(out$means,variation="SD",horiz=TRUE,xlim=c(0,45),bar=FALSE, col=colors()[25],space=2, main="Standard deviation",las=1) bar.err(out$means,variation="SE",horiz=FALSE,ylim=c(0,45),bar=FALSE, col=colors()[15],space=2,main="SE",las=1) bar.err(out$means,variation="range",ylim=c(0,45),bar=FALSE,col="green", space=3,main="Range = Max - Min",las=1) bar.group(out$groups,horiz=FALSE,ylim=c(0,45),density=8,col="red", main="Groups",las=1) #endgraph # Old version HSD.test() df<-df.residual(model) MSerror<-deviance(model)/df Fc<-anova(model)["virus",4] out <- with(sweetpotato,waller.test(yield, virus, df, MSerror, Fc, group=TRUE)) print(out)