Analysis of the Partially Balanced Incomplete Block Design

Source: R/PBIB.test.R

Analysis of variance PBIB and comparison mean adjusted. Applied to resoluble designs: Lattices and alpha design.

PBIB.test(
  block,
  trt,
  replication,
  y,
  k,
  method = c("REML", "ML", "VC"),
  test = c("lsd", "tukey"),
  alpha = 0.05,
  console = FALSE,
  group = TRUE
)

Arguments

block

blocks
trt

Treatment
replication

Replication
y

Response
k

Block size
method

Estimation method: REML, ML and VC
test

Comparison treatments
alpha

Significant test
console

logical, print output
group

logical, groups

Value

ANOVA

Analysis of variance

method

Estimation method: REML, ML and VC

parameters

Design parameters

statistics

Statistics of the model

model

Object: estimation model

Fstat

Criterion AIC and BIC

comparison

Comparison between treatments

means

Statistical summary of the study variable

groups

Formation of treatment groups

vartau

Variance-Covariance Matrix

Details

Method of comparison treatment. lsd: least significant difference. tukey: Honestly significant difference. Estimate: specifies the estimation method for the covariance parameters. The REML is the default method. The REML specification performs residual (restricted) maximum likelihood, and The ML specification performs maximum likelihood, and the VC specifications apply only to variance component models.

References

1. Iterative Analysis of Generalizad Lattice Designs. E.R. Williams (1977) Austral J. Statistics 19(1) 39-42.

2. Experimental design. Cochran and Cox. Second edition. Wiley Classics Library Edition published 1992

See also

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

Examples


require(agricolae)
# alpha design 
Genotype<-c(paste("gen0",1:9,sep=""),paste("gen",10:30,sep=""))
ntr<-length(Genotype)
r<-2
k<-3
s<-10
obs<-ntr*r
b <- s*r
book<-design.alpha(Genotype,k,r,seed=5)
#> 
#> Alpha Design (0,1) - Serie  I 
#> 
#> Parameters Alpha Design
#> =======================
#> Treatmeans : 30
#> Block size : 3
#> Blocks     : 10
#> Replication: 2 
#> 
#> Efficiency factor
#> (E ) 0.6170213 
#> 
#> <<< Book >>>
book$book[,3]<- gl(20,3)
dbook<-book$book
# dataset
yield<-c(5,2,7,6,4,9,7,6,7,9,6,2,1,1,3,2,4,6,7,9,8,7,6,4,3,2,2,1,1,2,
     1,1,2,4,5,6,7,8,6,5,4,3,1,1,2,5,4,2,7,6,6,5,6,4,5,7,6,5,5,4)
rm(Genotype)
# not run
# analysis
# require(nlme) # method = REML or LM in PBIB.test and require(MASS) method=VC
model <- with(dbook,PBIB.test(block, Genotype, replication, yield, k=3, method="VC"))
#> Error in eval(predvars, data, env): object 'yield' not found
# model$ANOVA
# plot(model,las=2)