cochran.eelworms {agridat} | R Documentation

## Counts of eelworms before and after fumigant treatments

### Description

Counts of eelworms before and after fumigant treatments

### Format

A data frame with 48 observations on the following 7 variables.

`block`

  block factor, 4 levels

`row`

  row

`col`

  column

`fumigant`

  fumigant factor

`dose`

  dose, Numeric 0,1,2. Maybe should be a factor?

`initial`

  count of eelworms pre-treatment

`final`

  count of eelworms post-treatment

### Details

In the original experiment plan (as shown in Bailey 2008), columns 9, 10, 11 are shifted up slightly.

Treatment codes: Con = Control, Chl = Chlorodinitrobenzen, Cym = Cymag, Car = Carbon Disulphide jelly, See = Seekay.

Experiment was conducted in 1935 at Rothamsted Experiment Station. In early March 400 grams of soil were sampled and the number of eelworm cysts were counted. Fumigants were added to the soil, oats were sown and later harvested. In October, the plots were again sampled and the final count of cysts recorded.

### Source

Cochran and Cox, 1950. Experimental Designs. Table 3.1.

### References

R. A. Bailey, 2008. Design of Comparative Experiments. Cambridge.

### Examples

    data(cochran.eelworms)
    dat <- cochran.eelworms

    # Very strong spatial trends
    if(require(desplot)){
      desplot(initial ~ col*row, data=dat,
              flip=TRUE, # aspect unknown
              main="cochran.eelworms")
    }

    # final counts are strongly related to initial counts
    require(lattice)
    xyplot(final~initial|factor(dose), data=dat, group=fumigant,
           main="cochran.eelworms - by dose (panel) & fumigant",
           xlab="Initial worm count",
           ylab="Final worm count", auto.key=list(columns=5))

    # One approach...log transform, use 'initial' as covariate, create 9 treatments
    dat <- transform(dat, trt=factor(paste0(fumigant, dose)))
    m1 <- aov(log(final) ~ block + trt + log(initial), data=dat)
    anova(m1)

[Package agridat version 1.16 Index]