R version 2.4.0 beta (2006-09-25 r39510)
Copyright (C) 2006 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

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> library(mlmRev)
Loading required package: lme4
Loading required package: Matrix
Loading required package: lattice
> options(show.signif.stars = FALSE)
> cntr <- list()
> #cntr <- list(EMverbose = TRUE, msVerbose = 1) # uncomment for verbose output
> (fm1 <- lmer(attain ~ verbal * sex + (1|primary) + (1|second), ScotsSec,
+              control = cntr))
Linear mixed-effects model fit by REML 
Formula: attain ~ verbal * sex + (1 | primary) + (1 | second) 
   Data: ScotsSec 
   AIC   BIC logLik MLdeviance REMLdeviance
 14880 14917  -7434      14843        14868
Random effects:
 Groups   Name        Variance Std.Dev.
 primary  (Intercept) 0.275457 0.52484 
 second   (Intercept) 0.014747 0.12144 
 Residual             4.253113 2.06231 
number of obs: 3435, groups: primary, 148; second, 19

Fixed effects:
            Estimate Std. Error t value
(Intercept) 5.914713   0.076795   77.02
verbal      0.158356   0.003787   41.81
sexF        0.121553   0.072413    1.68
verbal:sexF 0.002593   0.005388    0.48

Correlation of Fixed Effects:
            (Intr) verbal sexF  
verbal       0.177              
sexF        -0.482 -0.178       
verbal:sexF -0.122 -0.680  0.161
> (fm2 <- lmer(attain ~ verbal * sex + (1|primary) + (1|second), ScotsSec,
+              control = c(cntr, list(niterEM = 40))))
Linear mixed-effects model fit by REML 
Formula: attain ~ verbal * sex + (1 | primary) + (1 | second) 
   Data: ScotsSec 
   AIC   BIC logLik MLdeviance REMLdeviance
 14880 14917  -7434      14843        14868
Random effects:
 Groups   Name        Variance Std.Dev.
 primary  (Intercept) 0.275458 0.52484 
 second   (Intercept) 0.014749 0.12144 
 Residual             4.253112 2.06231 
number of obs: 3435, groups: primary, 148; second, 19

Fixed effects:
            Estimate Std. Error t value
(Intercept) 5.914713   0.076795   77.02
verbal      0.158355   0.003787   41.81
sexF        0.121553   0.072413    1.68
verbal:sexF 0.002593   0.005388    0.48

Correlation of Fixed Effects:
            (Intr) verbal sexF  
verbal       0.177              
sexF        -0.482 -0.178       
verbal:sexF -0.122 -0.680  0.161
> ## fm1 and fm2 should be essentially identical when optimizing with nlminb
> ## The fits are substantially different when optimizing with optim
> q("no")