R Under development (unstable) (2013-09-09 r63889) -- "Unsuffered Consequences"
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> #### Saved fits for lme4 testing
> ####  ----------------------------------
> fn <- system.file("testdata/lme-tst-fits.rda", package="lme4", mustWork=TRUE)
> if(FALSE) ### "Load" these by
+     load(fn)
> 
> library(lme4)
Loading required package: lattice
Loading required package: Matrix
> ## intercept only in both fixed and random effects
> fit_sleepstudy_0 <- lmer(Reaction ~ 1 + (1|Subject), sleepstudy)
> ## fixed slope, intercept-only RE
> fit_sleepstudy_1 <- lmer(Reaction ~ Days + (1|Subject), sleepstudy)
> ## fixed slope, intercept & slope RE
> fit_sleepstudy_2 <- lmer(Reaction ~ Days + (Days|Subject), sleepstudy)
> ## fixed slope, independent intercept & slope RE
> fit_sleepstudy_3 <- lmer(Reaction ~ Days + (1|Subject)+
+                          (0+Days|Subject), sleepstudy)
> 
> save(list=ls(pattern="fit_sleepstudy"),file="lme-tst-fits.rda")
> 
> load("lme-tst-fits.rda")
> cbpp$obs <- factor(seq(nrow(cbpp)))
> fit_cbpp_0 <- glmer(cbind(incidence,size-incidence) ~ 1 + (1|herd),
+                     cbpp, family=binomial)
> fit_cbpp_1 <- update(fit_cbpp_0, . ~ . + period)
> fit_cbpp_2 <- update(fit_cbpp_1, . ~ . + (1|obs))
> fit_cbpp_3 <- update(fit_cbpp_0,
+                      formula=incidence/size ~ period + (1 | herd),
+                      weights=size)
> save(list=ls(pattern="fit_"),file="lme-tst-fits.rda")
> 
> ## an example with >20 fixed effects:
> if (require(agridat)) {
+     dat <- archbold.apple
+     ## Define main plot and subplot
+     dat <- transform(dat, rep=factor(rep),
+                      spacing=factor(spacing), trt=factor(trt),
+                      mp = factor(paste(row,spacing,sep="")),
+                      sp = factor(paste(row,spacing,stock,sep="")))
+     fit_agridat_archbold <- lmer(yield ~ -1 + trt + (1|rep/mp/sp), dat)
+     save(list=ls(pattern="fit_"),file="lme-tst-fits.rda")
+ }
Loading required package: agridat
Loading required package: grid
Loading required package: reshape2
> 
> 
> proc.time()
   user  system elapsed 
  5.108   3.640   9.811