R version 4.4.0 alpha (2024-03-26 r86209 ucrt)
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-w64-mingw32/x64

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library("lme4")
Loading required package: Matrix
> L <- load(system.file("testdata","crabs_randdata2.Rda",package="lme4"))
> ## randdata0: simulated data, in form suitable for plotting
> ## randdata: simulated data, in form suitable for analysis
> 
> ## fr  ## alive/dead formula
> ## fr2 ## proportion alive formula (use with weights=initial.snail.density)
> 
> ## FIXME: there are still bigger differences than I'd like between the approaches
> ## (mostly in the random-effects correlation).  It's not clear who's right;
> ## lme4 thinks its parameters are better, but ??  Could be explored further.
> 
> if (FALSE) {
+ ## library(ggplot2)  ## commented to avoid triggering Suggests: requirement
+ library(grid)
+ zmargin <- theme(panel.margin=unit(0,"lines"))
+ theme_set(theme_bw())
+ g1 <- ggplot(randdata0,aes(x=snail.size,y=surv,colour=snail.size,fill=snail.size))+
+     geom_hline(yintercept=1,colour="black")+
+     stat_sum(aes(size=factor(..n..)),alpha=0.6)+
+     facet_grid(.~ttt)+zmargin+
+     geom_boxplot(fill=NA,outlier.colour=NULL,outlier.shape=3)+  ## set outliers to same colour as points
+     ## (hard to see which are outliers, but it doesn't really matter in this case)
+     scale_size_discrete("# obs",range=c(2,5))
+ }
> 
> if (.Platform$OS.type != "windows") {
+ t1 <- system.time(glmer1 <- glmer(fr2,weights=initial.snail.density,
+                                   family ="binomial", data=randdata))
+ t1B <- system.time(glmer1B <- glmer(fr,family ="binomial", data=randdata))
+ 
+ res1 <- c(fixef(glmer1),c(VarCorr(glmer1)$plot))
+ res1B <- c(fixef(glmer1B),c(VarCorr(glmer1B)$plot))
+ p1 <- unlist(getME(glmer1,c("theta","beta")))
+ stopifnot(all.equal(res1,res1B))
+ 
+ dfun <- update(glmer1,devFunOnly=TRUE)
+ stopifnot(all.equal(dfun(p1),c(-2*logLik(glmer1))))
+ ##
+ ## library(lme4.0)  ## version 0.999999.2 results
+ ## t1_lme4.0 <- system.time(glmer1X <-
+ ##                           glmer(fr2,weights=initial.snail.density,
+ ##                                 family ="binomial", data=randdata))
+ ## dput(c(fixef(glmer1X),c(VarCorr(glmer1X)$plot)))
+ ## p1X <- c(getME(glmer1X,"theta"),getME(glmer1X,"beta"))
+ p1X <- c(0.681301656652347, -1.14775239687404, 0.436143018123226, 
+ 2.77730476938968, 0.609023583738824, -1.60055813739844, 2.0324468778545, 
+ 0.624173873057839, -1.7908793509579, -2.44540201631615, -1.42365990002708, 
+ -2.26780929006268, 0.700928084600075, -1.26220238391029, 0.369024582097804, 
+ 3.44325347343035, 2.26400391093108)
+ stopifnot(all.equal(unname(p1),p1X,tolerance=0.03))
+ dfun(p1X)
+ dfun(p1)
+ ## ~ 1.8 seconds elapsed time
+ lme4.0_res <- 
+     structure(c(2.77730476938968, 0.609023583738824, -1.60055813739844, 
+                 2.0324468778545, 0.624173873057839, -1.7908793509579, -2.44540201631615, 
+                 -1.42365990002708, -2.26780929006268, 0.700928084600075, -1.26220238391029, 
+                 0.369024582097804, 3.44325347343035, 2.26400391093108, 0.464171947357232, 
+                 -0.532754465140956, -0.532754465140956, 0.801690946568518),
+           .Names = c("(Intercept)", 
+           "crab.speciesS", "crab.speciesW", "crab.sizeS", "crab.sizeM", 
+           "snail.sizeS", "crab.speciesS:crab.sizeS", "crab.speciesS:crab.sizeM", 
+           "crab.speciesS:snail.sizeS", "crab.speciesW:snail.sizeS",
+           "crab.sizeS:snail.sizeS", "crab.sizeM:snail.sizeS",
+           "crab.speciesS:crab.sizeS:snail.sizeS", 
+           "crab.speciesS:crab.sizeM:snail.sizeS", "", "", "", ""))
+ 
+ stopifnot(all.equal(res1,lme4.0_res,tolerance=0.015))
+ 
+ 
+ ## library("glmmADMB")
+ ## prop/weights formulation: ~ 7 seconds
+ ## t1_glmmadmb <- system.time(glmer1B <- glmmadmb(fr,family ="binomial",
+ ##                                               corStruct="full",data=randdata))
+ ## dput(c(fixef(glmer1B),c(VarCorr(glmer1B)$plot)))
+ glmmADMB_res <- structure(c(2.7773101267224, 0.609026276823218, -1.60055704634712, 
+ 2.03244174458562, 0.624171008585953, -1.79088398816641, -2.44540300134182, 
+ -1.42366043619683, -2.26780858382505, 0.700927141726545, -1.26219964572264, 
+ 0.369029052442189, 3.44326297908383, 2.26403738918967, 0.46417, 
+ -0.53253, -0.53253, 0.80169), .Names = c("(Intercept)", "crab.speciesS", 
+ "crab.speciesW", "crab.sizeS", "crab.sizeM", "snail.sizeS", "crab.speciesS:crab.sizeS", 
+ "crab.speciesS:crab.sizeM", "crab.speciesS:snail.sizeS", "crab.speciesW:snail.sizeS", 
+ "crab.sizeS:snail.sizeS", "crab.sizeM:snail.sizeS", "crab.speciesS:crab.sizeS:snail.sizeS", 
+ "crab.speciesS:crab.sizeM:snail.sizeS", "", "", "", ""))
+ 
+ stopifnot(all.equal(res1B,glmmADMB_res,tolerance=0.015))
+ } ## skip on windows (for speed)
> 
> proc.time()
   user  system elapsed 
   1.51    0.29    1.79