Multi-environment trial of cereal with lodging data

Percent lodging is given for 32 genotypes at 7 environments.

Format

A data frame with 224 observations on the following 3 variables.

env

environment, 1-7

gen

genotype, 1-32

y

percent lodged

Details

This data is for the first year of a three-year study.

Used with permission of Chris Glasbey.

Source

D. J. Allcroft and C. A. Glasbey, 2003. Analysis of crop lodging using a latent variable model. Journal of Agricultural Science, 140, 383--393. https://doi.org/10.1017/S0021859603003332

Examples

# \dontrun{

library(agridat)
data(allcroft.lodging)
dat <- allcroft.lodging

# Transformation
dat$sy <- sqrt(dat$y)
# Variety 4 has no lodging anywhere, so add a small amount
dat[dat$env=='E5' & dat$gen=='G04',]$sy <- .01

libs(lattice)
dotplot(env~y|gen, dat, as.table=TRUE,
        xlab="Percent lodged (by genotype)", ylab="Variety",
        main="allcroft.lodging")

# Tobit model
libs(AER)
#> Loading required package: car
#> Loading required package: carData
#> Loading required package: lmtest
#> Loading required package: zoo
#> 
#> Attaching package: 'zoo'
#> The following objects are masked from 'package:base':
#> 
#>     as.Date, as.Date.numeric
#> Loading required package: sandwich
#> Loading required package: survival
m3 <- tobit(sy ~ 1 + gen + env, left=0, right=100, data=dat)

# Table 2 trial/variety means
preds <- expand.grid(gen=levels(dat$gen), env=levels(dat$env))
preds$pred <- predict(m3, newdata=preds)
round(tapply(preds$pred, preds$gen, mean),2)
#>   G01   G02   G03   G04   G05   G06   G07   G08   G09   G10   G11   G12   G13 
#> -0.52 -2.77  1.68 -3.63 -2.57 -0.32 -2.27  0.94 -0.82 -2.95 -2.35 -2.95 -0.48 
#>   G14   G15   G16   G17   G18   G19   G20   G21   G22   G23   G24   G25   G26 
#> -1.45  0.72  0.35 -0.48 -2.29  0.08 -2.70 -1.31 -1.47  1.23 -0.66 -0.32 -2.08 
#>   G27   G28   G29   G30   G31   G32 
#> -1.66  0.19 -0.92  0.86  0.16  0.87 
round(tapply(preds$pred, preds$env, mean),2)
#>    E1    E2    E3    E4    E5    E6    E7 
#> -0.03 -2.48 -2.37 -0.60  2.47 -1.73 -1.79 

# }