Split-strip-plot of soybeans

Split-strip-plot of soybeans

Format

A data frame with 160 observations on the following 8 variables.

block

block factor, 4 levels

plot

plot number

cultivar

cultivar factor, 4 levels

spacing

row spacing

pop

population (thousand per acre)

yield

yield

row

row

col

column

Details

Within each block, cultivars were whole plots. Withing whole plots, spacing was applied in strips vertically, and population was applied in strips horizontally.

Used with permission of David Holshouser at Virginia Polytechnic.

Source

Schabenberger, Oliver and Francis J. Pierce. 2002. Contemporary Statistical Models for the Plant and Soil Sciences CRC Press, Boca Raton, FL. Page 493.

Examples

# \dontrun{
  
library(agridat)
data(holshouser.splitstrip)
dat <- holshouser.splitstrip
dat$spacing <- factor(dat$spacing)
dat$pop <- factor(dat$pop)

# Experiment layout and field trends
  libs(desplot)
  desplot(dat, yield ~ col*row,
          out1=block, # unknown aspect
          main="holshouser.splitstrip")
  desplot(dat, spacing ~ col*row,
          out1=block, out2=cultivar, # unknown aspect
          col=cultivar, text=pop, cex=.8, shorten='none', col.regions=c('wheat','white'),
          main="holshouser.splitstrip experiment design")


# Overall main effects and interactions
  libs(HH)
#> Loading required package: grid
#> Loading required package: multcomp
#> Loading required package: mvtnorm
#> Loading required package: survival
#> 
#> Attaching package: 'survival'
#> The following object is masked from 'package:boot':
#> 
#>     aml
#> The following object is masked from 'package:asreml':
#> 
#>     rats
#> Loading required package: TH.data
#> 
#> Attaching package: 'TH.data'
#> The following object is masked from 'package:MASS':
#> 
#>     geyser
#> Loading required package: gridExtra
#> 
#> Attaching package: 'gridExtra'
#> The following object is masked from 'package:dplyr':
#> 
#>     combine
#> 
#> Attaching package: 'HH'
#> The following object is masked from 'package:boot':
#> 
#>     logit
#> The following objects are masked from 'package:car':
#> 
#>     logit, vif
  interaction2wt(yield~cultivar*spacing*pop, dat,
                 x.between=0, y.between=0,
                 main="holshouser.splitstrip")


  ## Schabenberger's SAS model, page 497
  ## proc mixed data=splitstripplot;
  ##   class block cultivar pop spacing;
  ##   model yield = cultivar spacing spacing*cultivar pop pop*cultivar
  ##                 spacing*pop spacing*pop*cultivar / ddfm=satterth;
  ##   random block block*cultivar block*cultivar*spacing block*cultivar*pop;
  ## run;

  
  ## Now lme4. This design has five error terms--four are explicitly given.
  libs(lme4)
  libs(lucid)
  m1 <- lmer(yield ~ cultivar * spacing * pop +
               (1|block) + (1|block:cultivar) + (1|block:cultivar:spacing) +
               (1|block:cultivar:pop), data=dat)
  vc(m1) ## Variances match Schabenberger, page 498.
#>                     grp        var1 var2   vcov  sdcor
#>      block:cultivar:pop (Intercept) <NA> 2.421  1.556 
#>  block:cultivar:spacing (Intercept) <NA> 1.244  1.116 
#>          block:cultivar (Intercept) <NA> 0.4523 0.6725
#>                   block (Intercept) <NA> 3.037  1.743 
#>                Residual        <NA> <NA> 3.928  1.982 
  ##                    grp        var1 var2   vcov  sdcor
  ##     block:cultivar:pop (Intercept) <NA> 2.421  1.556
  ## block:cultivar:spacing (Intercept) <NA> 1.244  1.116
  ##         block:cultivar (Intercept) <NA> 0.4523 0.6725
  ##                  block (Intercept) <NA> 3.037  1.743
  ##               Residual        <NA> <NA> 3.928  1.982
  
# }