besag.triticale {agridat} | R Documentation

## Four-way factorial agronomic experiment in triticale

### Description

Four-way factorial agronomic experiment in triticale

### Usage

    data("besag.triticale")

### Format

A data frame with 54 observations on the following 7 variables.

`yield`

  yield, g/m^2

`row`

  row

`col`

  column

`gen`

  genotype / variety, 3 levels

`rate`

  seeding rate, kg/ha

`nitro`

  nitrogen rate, kw/ha

`regulator`

  growth regulator, 3 levels

### Details

Experiment conducted as a factorial on the yields of triticale. Fully randomized. Plots were 1.5m x 5.5m, but the orientation is not clear.

Besag and Kempton show how accounting for neighbors changes non-significant genotype differences into significant differences.

### Source

Julian Besag and Rob Kempton (1986). Statistical Analysis of Field Experiments Using Neighbouring Plots. Biometrics, 42, 231-251. Table 2. http://doi.org/10.2307/2531047

### References

None.

### Examples

    data(besag.triticale)
    dat <- besag.triticale

    if(require(desplot)){
      desplot(yield ~ col*row, data=dat,
              # aspect unknown
              main="besag.triticale")
    }

    ## Not run:
      # Besag & Kempton are not perfectly clear on the model, but
      # indicate that there was no evidence of any two-way interactions.
      # A reduced, main-effect model had genotype effects that were
      # "close to significant" at the five percent level.
      # The model below has p-value of gen at .04, so must be slightly
      # different than their model.
      dat <- transform(dat, rate=factor(rate), nitro=factor(nitro))
      dat <- transform(dat, xf=factor(col), yf=factor(row))
      m2 <- lm(yield ~ gen + rate + nitro + regulator + yf, data=dat)
      anova(m2)

      # Similar, but not exact, to Besag figure 5
      dat$res <- resid(m2)
      require(lattice)
      xyplot(res ~ col|as.character(row), data=dat,
             as.table=TRUE, type="s", layout=c(1,3),
             main="besag.triticale")

    ## End(Not run)

    # ----------------------------------------------------------------------------

    ## Not run:
      # asreml3
      require(asreml)

      # Besag uses an adjustment based on neighboring plots.
      # This analysis fits the standard AR1xAR1 residual model

      dat <- dat[order(dat$xf, dat$yf), ]
      m3 <- asreml(yield ~ gen + rate + nitro + regulator +
                     gen:rate + gen:nitro + gen:regulator +
                     rate:nitro + rate:regulator +
                     nitro:regulator + yf, data=dat,
                   rcov = ~ ar1(xf):ar1(yf))
      anova(m3) # Strongly significant gen, rate, regulator

    ## End(Not run)

    # ----------------------------------------------------------------------------

    ## Not run:
      ## require(asreml4)

      ## # Besag uses an adjustment based on neighboring plots.
      ## # This analysis fits the standard AR1xAR1 residual model

      ## dat <- dat[order(dat$xf, dat$yf), ]
      ## m3 <- asreml(yield ~ gen + rate + nitro + regulator +
      ##                gen:rate + gen:nitro + gen:regulator +
      ##                rate:nitro + rate:regulator +
      ##                nitro:regulator + yf, data=dat,
      ##              resid = ~ ar1(xf):ar1(yf))
      ## wald(m3) # Strongly significant gen, rate, regulator
      ## ##                 Df Sum of Sq Wald statistic Pr(Chisq)
      ## ## (Intercept)      1   1288255        103.971 < 2.2e-16 ***
      ## ## gen              2    903262         72.899 < 2.2e-16 ***
      ## ## rate             1    104774          8.456  0.003638 **
      ## ## nitro            1       282          0.023  0.880139
      ## ## regulator        2    231403         18.676 8.802e-05 ***
      ## ## yf               2      3788          0.306  0.858263
      ## ## gen:rate         2      1364          0.110  0.946461
      ## ## gen:nitro        2     30822          2.488  0.288289
      ## ## gen:regulator    4     37269          3.008  0.556507
      ## ## rate:nitro       1      1488          0.120  0.728954
      ## ## rate:regulator   2     49296          3.979  0.136795
      ## ## nitro:regulator  2     41019          3.311  0.191042
      ## ## residual (MS)          12391

    ## End(Not run)

[Package agridat version 1.16 Index]