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)
y |
Variable response |
trt |
Treatments |
DFerror |
Degrees of freedom |
MSerror |
Mean Square Error |
Fc |
F Value |
K |
K-RATIO |
group |
TRUE or FALSE |
main |
Title |
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.
y |
Numeric |
trt |
factor |
DFerror |
Numeric |
MSerror |
Numeric |
Fc |
Numeric |
K |
Numeric |
group |
Logic |
main |
Text |
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
HSD.test
, LSD.test
, bar.err
,
bar.group
library(agricolae) data(sweetpotato) attach(sweetpotato) model<-aov(yield~virus) df<-df.residual(model) MSerror<-deviance(model)/df Fc<-anova(model)[1,4] comparison <- waller.test(yield, virus, df, MSerror, Fc, group=TRUE, main="Yield of sweetpotato. Dealt with different virus") # std = F (default) is standard error #startgraph par(mfrow=c(2,2)) bar.err(comparison,std=TRUE,horiz=TRUE,xlim=c(0,45),density=4) bar.err(comparison,std=TRUE,horiz=FALSE,ylim=c(0,45),density=8,col="blue") bar.group(comparison,horiz=FALSE,ylim=c(0,45),density=8,col="red") bar.group(comparison,horiz=TRUE,xlim=c(0,45),density=4,col="green") #endgraph