Running examples in ‘afex-Ex.R’ failed
The error most likely occurred in:

> ### Name: mixed
> ### Title: p-values for fixed effects of mixed-model via lme4::lmer()
> ### Aliases: lmer_alt mixed
> 
> ### ** Examples
> 
> 
> ###########################
> ## Full Analysis Example ##
> ###########################
> 
> ## Not run: 
> ##D ### split-plot experiment (Singmann & Klauer, 2011, Exp. 2)
> ##D ## between-factor: instruction
> ##D ## within-factor: inference & type
> ##D ## hypothesis: three-way interaction
> ##D data("sk2011.2")
> ##D 
> ##D # use only affirmation problems (S&K also splitted the data like this)
> ##D sk2_aff <- droplevels(sk2011.2[sk2011.2$what == "affirmation",])
> ##D 
> ##D # set up model with maximal by-participant random slopes 
> ##D sk_m1 <- mixed(response ~ instruction*inference*type+(inference*type|id), sk2_aff)
> ##D 
> ##D sk_m1 # prints ANOVA table with nicely rounded numbers (i.e., as characters)
> ##D nice(sk_m1)  # returns the same but without printing potential warnings
> ##D anova(sk_m1) # returns and prints numeric ANOVA table (i.e., not-rounded)
> ##D summary(sk_m1) # lmer summary of full model
> ##D 
> ##D # suppressing correlation among random slopes:
> ##D # very similar results, but significantly faster and often better convergence. 
> ##D sk_m2 <- mixed(response ~ instruction*inference*type+(inference*type||id), sk2_aff,
> ##D                expand_re = TRUE)
> ##D sk_m2
> ##D 
> ##D ## mixed objects can be passed to lsmeans directly:
> ##D 
> ##D # recreates basically Figure 4 (S&K, 2011, upper panel)
> ##D # only the 4th and 6th x-axis position are flipped
> ##D lsmip(sk_m1, instruction~type+inference)
> ##D 
> ##D # set up reference grid for custom contrasts:
> ##D # this can be made faster via:
> ##D # lsm.options(disable.pbkrtest = TRUE)
> ##D (rg1 <- lsmeans(sk_m1, c("instruction", "type", "inference")))
> ##D 
> ##D # set up contrasts on reference grid:
> ##D contr_sk2 <- list(
> ##D   ded_validity_effect = c(rep(0, 4), 1, rep(0, 5), -1, 0),
> ##D   ind_validity_effect = c(rep(0, 5), 1, rep(0, 5), -1),
> ##D   counter_MP = c(rep(0, 4), 1, -1, rep(0, 6)),
> ##D   counter_AC = c(rep(0, 10), 1, -1)
> ##D )
> ##D 
> ##D # test the main double dissociation (see S&K, p. 268)
> ##D contrast(rg1, contr_sk2, adjust = "holm")
> ##D # only plausibility effect is not significant here.
> ## End(Not run)
> 
> ###################################################
> ## Replicating Maxwell & Delaney (2004) Examples ##
> ###################################################
> 
> ### replicate results from Table 15.4 (Maxwell & Delaney, 2004, p. 789)
> data(md_15.1)
> # random intercept plus slope
> (t15.4a <- mixed(iq ~ timecat + (1+time|id),data=md_15.1))
Contrasts set to contr.sum for the following variables: timecat, id
Fitting 2 (g)lmer() models:
[..]
Obtaining 1 p-values:
[
 *** caught segfault ***
address 30, cause 'memory not mapped'

Traceback:
 1: La.svd(x, nu, nv)
 2: svd(x, 0, 0)
 3: diff(sval)
 4: stopifnot(diff(sval) <= 0)
 5: rankMatrix(cbind(Xlarge, Xsmall))
 6: KRmodcomp_init.lmerMod(largeModel, smallModel, matrixOK = TRUE)
 7: KRmodcomp_init(largeModel, smallModel, matrixOK = TRUE)
 8: KRmodcomp.lmerMod(full.model, fits[[c]])
 9: KRmodcomp(full.model, fits[[c]])
10: mixed(iq ~ timecat + (1 + time | id), data = md_15.1)
An irrecoverable exception occurred. R is aborting now ...