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

> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: Examp2.5.2.1
> ### Title: Examp2.5.2.1 from Duchateau, L. and Janssen, P. and Rowlands, G.
> ###   J. (1998)._Linear Mixed Models. An Introduction with applications in
> ###   Veterinary Research_. International Livestock Research Institute.
> ### Aliases: Examp2.5.2.1
> ### Keywords: datasets
> 
> ### ** Examples
> 
> #-------------------------------------------------------------
> ## Example 2.5.2.1 p-68
> #-------------------------------------------------------------
>  # PROC MIXED DATA=ex125;
>  # CLASS drug dose region;
>  # MODEL pcv=drug dose drug*dose / solution covb;
>  # RANDOM region drug*region;
>  # LSMEANS drug*dose;
>  # RUN;
>  
> library(lme4)
Loading required package: Matrix
> str(ex125)
'data.frame':	24 obs. of  4 variables:
 $ Region: int  1 1 1 1 2 2 2 2 3 3 ...
 $ Drug  : Factor w/ 2 levels "BERENIL","samorin": 1 1 2 2 1 1 2 2 1 1 ...
 $ dose  : Factor w/ 2 levels "h","l": 1 2 1 2 1 2 1 2 1 2 ...
 $ Pcv   : num  22.6 21.8 19.1 16.4 29 28.8 25.3 18.2 24 23.7 ...
> 
> fm2.10 <- 
+   lme4::lmer(
+          formula    = Pcv ~ dose*Drug + (1|Region/Drug)
+        , data       = ex125
+        , REML       = TRUE
+        , control    = lmerControl()
+        , start      = NULL
+        , verbose    = 0L
+     #  , subset
+     #  , weights
+     #  , na.action
+     #  , offset
+        , contrasts  = list(dose = "contr.SAS", Drug = "contr.SAS")
+        , devFunOnly = FALSE
+     #  , ...
+        )                       
> summary(fm2.10)
Linear mixed model fit by REML ['lmerMod']
Formula: Pcv ~ dose * Drug + (1 | Region/Drug)
   Data: ex125

REML criterion at convergence: 92.4

Scaled residuals: 
     Min       1Q   Median       3Q      Max 
-1.71077 -0.51628  0.08414  0.70276  1.16129 

Random effects:
 Groups      Name        Variance Std.Dev.
 Drug:Region (Intercept) 0.387    0.6221  
 Region      (Intercept) 5.151    2.2695  
 Residual                2.096    1.4479  
Number of obs: 24, groups:  Drug:Region, 12; Region, 6

Fixed effects:
                  Estimate Std. Error t value
(Intercept)        17.1333     1.1280  15.189
doseh               4.3500     0.8359   5.204
DrugBERENIL         7.1500     0.9098   7.859
doseh:DrugBERENIL  -3.1833     1.1822  -2.693

Correlation of Fixed Effects:
            (Intr) doseh  DBEREN
doseh       -0.371              
DrugBERENIL -0.403  0.459       
ds:DBERENIL  0.262 -0.707 -0.650
> anova(fm2.10)
Analysis of Variance Table
          Df Sum Sq Mean Sq F value
dose       1  45.65   45.65 21.7755
Drug       1 135.39  135.39 64.5796
dose:Drug  1  15.20   15.20  7.2507
> summary(fm2.10)$vcov
4 x 4 Matrix of class "dpoMatrix"
                  (Intercept)      doseh DrugBERENIL doseh:DrugBERENIL
(Intercept)         1.2723750 -0.3494028  -0.4139028         0.3494028
doseh              -0.3494028  0.6988055   0.3494028        -0.6988055
DrugBERENIL        -0.4139028  0.3494028   0.8278056        -0.6988055
doseh:DrugBERENIL   0.3494028 -0.6988055  -0.6988055         1.3976111
> library(lmerTest)  

Attaching package: ‘lmerTest’

The following object is masked from ‘package:lme4’:

    lmer

The following object is masked from ‘package:stats’:

    step

> lmerTest::lsmeansLT(model = fm2.10, test.effs="dose:Drug")
Error in UseMethod("lsmeansLT") : 
  no applicable method for 'lsmeansLT' applied to an object of class "c('lmerMod', 'merMod')"
Calls: <Anonymous>
Execution halted