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

if (FALSE) { # \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)
  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
  
} # }