Split-block experiment of sugar beets — little.splitblock • agridat

Split-block experiment of sugar beets.

data("little.splitblock")

Format

A data frame with 80 observations on the following 6 variables.

row: row
col: column
yield: sugar beet yield, tons/acre
harvest: harvest date, weeks after planting
nitro: nitrogen, pounds/acre
block: block

Details

Four rates of nitrogen, laid out as a 4x4 Latin-square experiment.

Within each column block, the sub-plots are strips (across 4 rows) of 5 different harvest dates.

The use of sub-plots a s strips necessitates care when determining the error terms in the ANOVA table.

Note, Little has yield value of 22.3 for row 3, column I-H3. This data uses 23.3 in order to match the marginal totals given by Little.

Source

Thomas M. Little, F. Jackson Hills. (1978) Agricultural Experimentation

References

None.

Examples

# \dontrun{

library(agridat)
data(little.splitblock)
dat <- little.splitblock

# Match marginal totals given by Little.
## sum(dat$yield)
## with(dat, tapply(yield,col,sum))
## with(dat, tapply(yield,row,sum))

# Layout shown by Little figure 10.2
libs(desplot)
desplot(dat, yield ~ col*row,
        out1=block, out2=col, col=nitro, cex=1, num=harvest,
        main="little.splitblock")


# Convert continuous traits to factors
dat <- transform(dat, R=factor(row), C=factor(block),
                 H=factor(harvest), N=factor(nitro))

if(0){
  libs(lattice)
  xyplot(yield ~ nitro|H,dat)
  xyplot(yield ~ harvest|N,dat)
}

# Anova table matches Little, table 10.3
m1 <- aov(yield ~ R + C + N + H + N:H +
            Error(R:C:N + C:H + C:N:H), data=dat)
#> Warning: Error() model is singular
summary(m1)
#> 
#> Error: C:H
#>           Df Sum Sq Mean Sq F value   Pr(>F)    
#> C          3     58    19.4   2.326    0.126    
#> H          4   3719   929.6 111.711 2.19e-09 ***
#> Residuals 12    100     8.3                     
#> ---
#> Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
#> 
#> Error: R:C:N
#>           Df Sum Sq Mean Sq F value  Pr(>F)   
#> R          3  224.7    74.9   3.755 0.07888 . 
#> N          3 1101.3   367.1  18.406 0.00198 **
#> Residuals  6  119.7    19.9                   
#> ---
#> Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
#> 
#> Error: C:N:H
#>           Df Sum Sq Mean Sq F value   Pr(>F)    
#> N:H       12 157.68  13.140   6.497 5.61e-06 ***
#> Residuals 36  72.81   2.022                     
#> ---
#> Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

# }