gomez.wetdry {agridat} | R Documentation

## Rice yield in wet & dry seasons with nitrogen fertilizer treatments

### Description

Rice yield in wet & dry seasons with nitrogen fertilizer treatments

### Format

A data frame with 96 observations on the following 4 variables.

`season`

  season = wet/dry

`nitrogen`

  nitrogen fertilizer kg/ha

`rep`

  replicate

`yield`

  grain yield, t/ha

### Details

Five nitrogen fertilizer treatments were tested in 2 seasons using 3 reps.

### Source

Gomez, K.A. and Gomez, A.A.. 1984, Statistical Procedures for Agricultural Research. Wiley-Interscience. Page 318.

Used with permission of Kwanchai Gomez.

### References

Rong-Cai Yang, Patricia Juskiw. (2011). Analysis of covariance in agronomy and crop research. Canadian Journal of Plant Science, 91:621-641. http://doi.org/10.4141/cjps2010-032

### Examples

    data(gomez.wetdry)
    dat <- gomez.wetdry

    require(lattice)
    foo1 <- xyplot(yield ~ nitrogen|season, data=dat,
                   group=rep,type='l',auto.key=list(columns=3),
                   ylab="yield in each season",
                   main="gomez.wetdry raw data & model")

    # Yang & Juskiw fit a quadratic model with linear and quadratic
    # contrasts using non-equal intervals of nitrogen levels.
    # This example below omits the tedious contrasts

    if(require(latticeExtra) & require(lme4)){
      m1 <-lmer(yield ~ season*poly(nitrogen, 2) + (1|season:rep), data=dat)
      pdat <- expand.grid(season=c('dry','wet'),
                          nitrogen=seq(from=0,to=150,by=5))
      pdat$pred <- predict(m1, newdata=pdat, re.form= ~ 0)
      foo1 +
        xyplot(pred ~ nitrogen|season, data=pdat, type='l',lwd=2,col="black")
    } else {
      foo1
    }

    # m2 <-lmer(yield ~ poly(nitrogen, 2) + (1|season:rep), data=dat)
    # anova(m1,m2)
    ## m2: yield ~ poly(nitrogen, 2) + (1 | season:rep)
    ## m1: yield ~ season * poly(nitrogen, 2) + (1 | season:rep)
    ##    Df    AIC    BIC  logLik deviance  Chisq Chi Df Pr(>Chisq)
    ## m2  5 86.418 93.424 -38.209   76.418
    ## m1  8 64.216 75.425 -24.108   48.216 28.202      3  3.295e-06 ***

[Package agridat version 1.16 Index]