vaneeuwijk.nematodes {agridat} | R Documentation

## Number of cysts on 11 potato genotypes for 5 potato cyst nematode populations.

### Description

The number of cysts on 11 potato genotypes for 5 potato cyst nematode populations.

### Usage

    data("vaneeuwijk.nematodes")

### Format

A data frame with 55 observations on the following 3 variables.

`gen`

  potato genotype

`pop`

  nematode population

`y`

  number of cysts

### Details

The number of cysts on 11 potato genotypes for 5 potato cyst nematode populations belonging to the species Globodera pallida. This is part of a larger table in . The numbers are the means over four or five replicates.

Van Eeuwijk used this data to illustrate fitting a generalized linear model.

### Source

Fred A. van Eeuwijk, (1995). Multiplicative Interaction in Generalized Linear Models. Biometrics, 51, 1017-1032. http://doi.org/10.2307/2533001

### References

Arntzen, F.K. & van Eeuwijk (1992). Variation in resistance level of potato genotypes and virulence level of potato cyst nematode populations. Euphytica, 62, 135-143. http://doi.org/10.1007/BF00037939

### Examples

    library(agridat)
    data(vaneeuwijk.nematodes)
    dat <- vaneeuwijk.nematodes

    # show non-normality
    op <- par(mfrow=c(2,1), mar=c(5,4,3,2))
    boxplot(y ~ pop, data=dat, las=2,
            ylab="number of cysts")
    title("vaneeuwijk.nematodes - cysts per nematode pop")
    boxplot(y ~ gen, data=dat, las=2)
    title("vaneeuwijk.nematodes - cysts per potato")
    par(op)

    ## Not run:
      # normal distribution
      lm1 <- lm(y ~ gen + pop, data=dat)

      # poisson distribution
      glm1 <- glm(y ~ gen+pop,data=dat,family=quasipoisson(link=log))
      anova(glm1)

      require(gnm)

      # main-effects non-interaction model
      gnm0 <- gnm(y ~ pop + gen, data=dat,
                  family=quasipoisson(link=log))
      # one interaction
      gnm1 <- gnm(y ~ pop + gen + Mult(pop,gen,inst=1), data=dat,
                  family=quasipoisson(link=log))
      # two interactions
      gnm2 <- gnm(y ~ pop + gen + Mult(pop,gen,inst=1) + Mult(pop,gen,inst=2),
                  data=dat,
                  family=quasipoisson(link=log))

      # anova(gnm0, gnm1, gnm2, test="F")
      # only 2, not 3 axes needed

      # match vaneeuwijk table 2
      anova(gnm2)
      ##                          Df Deviance Resid. Df Resid. Dev
      ## NULL                                        54     8947.4
      ## pop                       4    690.6        50     8256.8
      ## gen                      10   7111.4        40     1145.4
      ## Mult(pop, gen, inst = 1) 13    716.0        27      429.4
      ## Mult(pop, gen, inst = 2) 11    351.1        16       78.3

      # compare residual qq plots from models
      op <- par(mfrow=c(2,2))
      plot(lm1, which=2, main="LM")
      plot(glm1, which=2, main="GLM")
      plot(gnm0, which=2, main="GNM, no interaction")
      plot(gnm2, which=2, main="GNM, 2 interactions")
      par(op)

      # extract interaction-term coefficients, make a biplot
      pops <- pickCoef(gnm2, "[.]pop")
      gens <- pickCoef(gnm2, "[.]gen")
      coefs <- coef(gnm2)
      A <- matrix(coefs[pops], nc = 2)
      B <- matrix(coefs[gens], nc = 2)
      A2=scale(A)
      B2=scale(B)
      rownames(A2) <- levels(dat$pop)
      rownames(B2) <- levels(dat$gen)
      # near-match with vaneeuwijk figure 1
      biplot(A2,B2, expand=2.5,xlim=c(-2,2),ylim=c(-2,2),
             main="vaneeuwijk.nematodes - GAMMI biplot")

    ## End(Not run)

[Package agridat version 1.16 Index]