R Under development (unstable) (2023-11-01 r85459 ucrt) -- "Unsuffered Consequences"
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> library(lme4)
Loading required package: Matrix
> library(testthat)
> 
> (testLevel <- lme4:::testLevel())
[1] 1
> L <- load(system.file("testdata/lme-tst-fits.rda",
+                       package="lme4", mustWork=TRUE))
> 
> if (testLevel>1) {
+ if (getRversion() > "3.0.0") {
+     ## saved fits are not safe with old R versions
+ 
+ fm1 <- fit_sleepstudy_1
+ 
+     
+ s1 <- simulate(fm1,seed=101)[[1]]
+ s2 <- simulate(fm1,seed=101,use.u=TRUE)
+ s3 <- simulate(fm1,seed=101,nsim=10)
+ s4 <- simulate(fm1,seed=101,use.u=TRUE,nsim=10)
+ stopifnot(length(s3)==10,all(sapply(s3,length)==180),
+           length(s4)==10,all(sapply(s4,length)==180))
+ 
+ ## binomial (2-column and prob/weights)
+ gm1 <- fit_cbpp_1
+ gm2 <- fit_cbpp_3
+ 
+ gm1_s1 <- simulate(gm1,seed=101)[[1]]
+ gm1_s2 <- simulate(gm2,seed=101)[[1]]
+ stopifnot(all.equal(gm1_s1[,1]/rowSums(gm1_s1),gm1_s2))
+ gm1_s3 <- simulate(gm1,seed=101,use.u=TRUE)
+ gm1_s4 <- simulate(gm1,seed=101,nsim=10)
+ gm1_s5 <- simulate(gm2,seed=101,nsim=10)
+ stopifnot(length(gm1_s4)==10,all(sapply(gm1_s4,ncol)==2),all(sapply(gm1_s4,nrow)==56))
+ stopifnot(length(gm1_s5)==10,all(sapply(gm1_s5,length)==56))
+ 
+ ## binomial (factor): Kubovy bug report 1 Aug 2013
+ d <- data.frame(y=factor(rep(letters[1:2],each=100)),
+                 f=factor(rep(1:10,10)))
+ g1 <- glmer(y~(1|f),data=d,family=binomial)
+ s6 <- simulate(g1,nsim=10)
+ stopifnot(length(s6)==10,all(sapply(s6,length)==200))
+ 
+ ## test explicitly stated link function
+ gm3 <- glmer(cbind(incidence, size - incidence) ~ period +
+              (1 | herd), data = cbpp, family = binomial(link="logit"))
+ s4 <- simulate(gm3,seed=101)[[1]]
+ stopifnot(all.equal(gm1_s1,s4))
+ 
+ cbpp$obs <- factor(seq(nrow(cbpp)))
+ gm4 <- fit_cbpp_2
+ ## glmer(cbind(incidence, size - incidence) ~ period +
+ ##             (1 | herd) + (1|obs), data = cbpp, family = binomial)
+ 
+ s5 <- simulate(gm4,seed=101)[[1]]
+ s6 <- simulate(gm4,seed=101,use.u=TRUE)[[1]]
+ 
+ ## Bernoulli
+ ## works, but too slow
+ if (testLevel > 2) {
+     if(require("mlmRev")) {
+         data(guImmun, package="mlmRev")
+         table(guImmun$immun)
+         ##    N    Y
+         ## 1195  964
+         g1i <- glmer(immun ~ kid2p+mom25p+ord+ethn+momEd+husEd+momWork+rural+pcInd81+
+                          (1|comm/mom), family="binomial", data=guImmun)
+         ## In checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv,  :
+         ##    Model failed to converge with max|grad| = 0.326795 (tol = 0.002, component 1)
+         sg1 <- simulate(g1i)
+         if(FALSE) { ## similar: not relevant here {comment out for 'R CMD check'}:
+         ## if(require("glmmTMB")) {
+             g2 <- glmmTMB(immun ~ kid2p+mom25p+ord+ethn+momEd+husEd+momWork+rural+pcInd81+
+                           (1|comm/mom), family="binomial", data=guImmun)
+             sg2 <- simulate(g2)
+         ## }
+         }
+     }
+ }
+ 
+ set.seed(101)
+ d <- data.frame(f = factor(rep(LETTERS[1:10],each=10)))
+ d$x <- runif(nrow(d))
+ u <- rnorm(10)
+ d$eta <- with(d, 1 + 2*x + u[f])
+ d$y <- rbinom(nrow(d), size=1, prob = plogis(d$eta))
+ 
+ g1 <- glmer(y ~ x + (1|f), data=d, family="binomial")
+ ## tolPwrss=1e-5: no longer necessary
+ 
+ if (testLevel > 2) { ## trying a set of  glmerControl(tolPwrss = 10^t) :
+   allcoef <- function(x) c(dev = deviance(x), th = getME(x,"theta"), beta = getME(x,"beta"))
+   tfun <- function(t) {
+       gg <- try( ## << errors (too small tolPwrss) are still printed :
+           glmer(y~x+(1|f),data=d,family="binomial",
+                     control = glmerControl(tolPwrss = 10^t)))
+     if (inherits(gg,"try-error")) rep(NA,4) else allcoef(gg)
+   }
+   tvec <- seq(-4,-16,by=-0.25)
+   tres <- cbind(t = tvec, t(sapply(tvec, tfun)))
+   print(tres)
+ }
+ 
+ gm_s5 <- simulate(g1, seed=102)[[1]]
+ 
+ d$y <- factor(c("N","Y")[d$y+1])
+ g1B <- glmer(y ~ x + (1|f), data=d, family="binomial") ## ,tolPwrss=1e-5)
+ s1B <- simulate(g1B, seed=102)[[1]]
+ stopifnot(all.equal(gm_s5,as.numeric(s1B)-1))
+ 
+ ## another Bernoulli
+ if(requireNamespace("mlmRev")) {
+     data(Contraception, package="mlmRev")
+     gm5 <- glmer(use ~ urban+age+livch+(1|district), Contraception, binomial)
+     s3 <- simulate(gm5)
+ }
+ d$y <- rpois(nrow(d),exp(d$eta))
+ gm6 <- glmer(y~x+(1|f),data=d,family="poisson")
+ s4 <- simulate(gm6)
+ 
+ ## simulation 'from scratch' with formulas:
+ ## binomial
+ ## form <- formula(gm1)[-2]
+ form <- ~ (1|herd) + period
+ gm1_s4 <- simulate(form,newdata=model.frame(gm1),
+                newparams=list(theta=getME(gm1,"theta"),
+                beta=fixef(gm1)),
+                family=binomial,
+                weights=rowSums(model.frame(gm1)[[1]]),
+                seed=101)[[1]]
+ stopifnot(all.equal(gm1_s2,gm1_s4))
+ 
+ gm1_s5 <- simulate(formula(gm1),newdata=cbpp,
+                newparams=list(theta=getME(gm1,"theta"),
+                beta=fixef(gm1)),
+                family=binomial,
+                seed=101)[[1]]
+ stopifnot(all.equal(gm1_s1,gm1_s5))
+ 
+ tt <- getME(gm1,"theta")
+ bb <- fixef(gm1)
+ expect_message(simulate(form,newdata=model.frame(gm1),
+                newparams=list(theta=unname(tt),
+                beta=fixef(gm1)),
+                family=binomial,
+                weights=rowSums(model.frame(gm1)[[1]]),
+                seed=101),"assuming same order")
+ expect_error(simulate(form,newdata=model.frame(gm1),
+                newparams=list(theta=setNames(tt,"abc"),
+                beta=fixef(gm1)),
+                family=binomial,
+                weights=rowSums(model.frame(gm1)[[1]]),
+                seed=101),"mismatch between")
+ expect_message(simulate(form,newdata=model.frame(gm1),
+                newparams=list(theta=tt,
+                beta=unname(bb)),
+                family=binomial,
+                weights=rowSums(model.frame(gm1)[[1]]),
+                seed=101),"assuming same order")
+ expect_error(simulate(form,newdata=model.frame(gm1),
+                newparams=list(theta=tt,
+                beta=setNames(bb,c("abc",names(bb)[-1]))),
+                family=binomial,
+                weights=rowSums(model.frame(gm1)[[1]]),
+                seed=101),"mismatch between")
+ 
+ ## Gaussian
+ form <- formula(fm1)[-2]
+ s7 <- simulate(form,newdata=model.frame(fm1),
+                newparams=list(theta=getME(fm1,"theta"),
+                beta=fixef(fm1),
+                sigma=sigma(fm1)),
+                family=gaussian,
+                seed=101)[[1]]
+ stopifnot(all.equal(s7,s1))
+ 
+ ## TO DO: wider range of tests, including offsets ...
+ 
+ }# R >= 3.0.0
+ } ## testLevel>1
> 
> proc.time()
   user  system elapsed 
   1.29    0.14    1.42