DAU.test: Finding the Variance Analysis of the Augmented block Design

Description

Analysis of variance Augmented block and comparison mean adjusted.

Usage

DAU.test(block, trt, y, method = c("lsd","tukey"),alpha=0.05,group=TRUE,console=FALSE)

Value

means: Statistical summary of the study variable
parameters: Design parameters
statistics: Statistics of the model
comparison: Comparison between treatments
groups: Formation of treatment groups
SE.difference: Standard error of:
Two Control Treatments
Two Augmented Treatments
Two Augmented Treatments(Different Blocks)
A Augmented Treatment and A Control Treatment
vartau: Variance-covariance matrix of the difference in treatments

Arguments

block: blocks
trt: Treatment
y: Response
method: Comparison treatments
alpha: Significant test
group: TRUE or FALSE
console: logical, print output

Author

F. de Mendiburu

Details

Method of comparison treatment. lsd: Least significant difference. tukey: Honestly significant differente. The controls can have different repetitions, at least two, do not use missing data.

References

Federer, W. T. (1956). Augmented (or hoonuiaku) designs. Hawaiian Planters, Record LV(2):191-208.

Examples

Run this code

library(agricolae)
block<-c(rep("I",7),rep("II",6),rep("III",7))
trt<-c("A","B","C","D","g","k","l","A","B","C","D","e","i","A","B","C","D","f","h","j")
yield<-c(83,77,78,78,70,75,74,79,81,81,91,79,78,92,79,87,81,89,96,82)
out<- DAU.test(block,trt,yield,method="lsd", group=TRUE)
print(out$groups)
plot(out)

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