agridat (version 1.16)

gomez.wetdry: 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.

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

# NOT RUN {
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 ***

# }