R Under development (unstable) (2026-01-12 r89300 ucrt) -- "Unsuffered Consequences"
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> # test_summary.R
> 
> # WRE says "using if(requireNamespace("pkgname")) is preferred, if possible."
> # even in tests:
> assertError <- function(expr, ...)
+   if(requireNamespace("tools")) tools::assertError(expr, ...) else invisible()
> assertWarning <- function(expr, ...)
+   if(requireNamespace("tools")) tools::assertWarning(expr, ...) else invisible()
> 
> # Kenward-Roger only available with pbkrtest and only then validated in R >= 3.3.3
> # (faulty results for R < 3.3.3 may be due to unstated dependencies in pbkrtest)
> has_pbkrtest <- requireNamespace("pbkrtest", quietly = TRUE) && getRversion() >= "3.3.3"
> 
> library(lmerTest)
Loading required package: lme4
Loading required package: Matrix

Attaching package: 'lmerTest'

The following object is masked from 'package:lme4':

    lmer

The following object is masked from 'package:stats':

    step

> 
> data("sleepstudy", package="lme4")
> data("cake", package="lme4")
> 
> # Fit basic model and compute summary:
> fm <- lmer(Reaction ~ Days + (1|Subject) + (0+Days|Subject), sleepstudy)
> (sfm <- summary(fm))
Linear mixed model fit by REML. t-tests use Satterthwaite's method [
lmerModLmerTest]
Formula: Reaction ~ Days + (1 | Subject) + (0 + Days | Subject)
   Data: sleepstudy

REML criterion at convergence: 1743.7

Scaled residuals: 
    Min      1Q  Median      3Q     Max 
-3.9626 -0.4625  0.0204  0.4653  5.1860 

Random effects:
 Groups    Name        Variance Std.Dev.
 Subject   (Intercept) 627.57   25.051  
 Subject.1 Days         35.86    5.988  
 Residual              653.58   25.565  
Number of obs: 180, groups:  Subject, 18

Fixed effects:
            Estimate Std. Error      df t value Pr(>|t|)    
(Intercept)  251.405      6.885  18.156  36.513  < 2e-16 ***
Days          10.467      1.560  18.156   6.712 2.59e-06 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Correlation of Fixed Effects:
     (Intr)
Days -0.184
> 
> ## Test class:
> stopifnot(all(
+   class(sfm) == c("summary.lmerModLmerTest", "summary.merMod"),
+   all(c("df", "Pr(>|t|)") %in% colnames(coef(sfm)))
+ ))
> stopifnot(class(summary(fm, ddf="lme4")) == "summary.merMod")
> 
> ## Test coefficient table names:
> mat <- coef(summary(fm))
> stopifnot(all( # colnames
+   colnames(mat) == c("Estimate", "Std. Error", "df", "t value", "Pr(>|t|)")
+ ))
> stopifnot(all( # rownames
+   names(fixef(fm)) == rownames(mat)
+ ))
> 
> ## Test pass of 'correlation' argument to lme4:::summary.merMod:
> x <- capture.output(summary(fm))
> x_nocor <- capture.output(summary(fm, correlation=FALSE))
> txt <- "Correlation of Fixed Effects:"
> stopifnot(
+   any(grep(txt, x)),
+   !any(grepl(txt, x_nocor))
+ )
> 
> # Test warning with unrecognized arguments (caught by lme4:::summary.merMod):
> assertWarning(summary(fm, false_arg=FALSE))
> 
> ## Test pass of extra arguments to lme4:::print.summary.merMod:
> x <- capture.output(print(summary(fm), signif.stars=TRUE))
> x_nocor <- capture.output(print(summary(fm), signif.stars=FALSE))
> txt <- "Signif. codes:"
> stopifnot(
+   any(grep(txt, x)),
+   !any(grepl(txt, x_nocor))
+ )
> 
> ####### ddf argument:
> (an1 <- summary(fm)) # Also testing print method.
Linear mixed model fit by REML. t-tests use Satterthwaite's method [
lmerModLmerTest]
Formula: Reaction ~ Days + (1 | Subject) + (0 + Days | Subject)
   Data: sleepstudy

REML criterion at convergence: 1743.7

Scaled residuals: 
    Min      1Q  Median      3Q     Max 
-3.9626 -0.4625  0.0204  0.4653  5.1860 

Random effects:
 Groups    Name        Variance Std.Dev.
 Subject   (Intercept) 627.57   25.051  
 Subject.1 Days         35.86    5.988  
 Residual              653.58   25.565  
Number of obs: 180, groups:  Subject, 18

Fixed effects:
            Estimate Std. Error      df t value Pr(>|t|)    
(Intercept)  251.405      6.885  18.156  36.513  < 2e-16 ***
Days          10.467      1.560  18.156   6.712 2.59e-06 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Correlation of Fixed Effects:
     (Intr)
Days -0.184
> (an2 <- summary(fm, ddf="Satterthwaite"))
Linear mixed model fit by REML. t-tests use Satterthwaite's method [
lmerModLmerTest]
Formula: Reaction ~ Days + (1 | Subject) + (0 + Days | Subject)
   Data: sleepstudy

REML criterion at convergence: 1743.7

Scaled residuals: 
    Min      1Q  Median      3Q     Max 
-3.9626 -0.4625  0.0204  0.4653  5.1860 

Random effects:
 Groups    Name        Variance Std.Dev.
 Subject   (Intercept) 627.57   25.051  
 Subject.1 Days         35.86    5.988  
 Residual              653.58   25.565  
Number of obs: 180, groups:  Subject, 18

Fixed effects:
            Estimate Std. Error      df t value Pr(>|t|)    
(Intercept)  251.405      6.885  18.156  36.513  < 2e-16 ***
Days          10.467      1.560  18.156   6.712 2.59e-06 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Correlation of Fixed Effects:
     (Intr)
Days -0.184
> stopifnot(isTRUE(
+   all.equal(an1, an2)
+ ))
> (an3 <- summary(fm, ddf="Sat")) ## Abbreviated argument
Linear mixed model fit by REML. t-tests use Satterthwaite's method [
lmerModLmerTest]
Formula: Reaction ~ Days + (1 | Subject) + (0 + Days | Subject)
   Data: sleepstudy

REML criterion at convergence: 1743.7

Scaled residuals: 
    Min      1Q  Median      3Q     Max 
-3.9626 -0.4625  0.0204  0.4653  5.1860 

Random effects:
 Groups    Name        Variance Std.Dev.
 Subject   (Intercept) 627.57   25.051  
 Subject.1 Days         35.86    5.988  
 Residual              653.58   25.565  
Number of obs: 180, groups:  Subject, 18

Fixed effects:
            Estimate Std. Error      df t value Pr(>|t|)    
(Intercept)  251.405      6.885  18.156  36.513  < 2e-16 ***
Days          10.467      1.560  18.156   6.712 2.59e-06 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Correlation of Fixed Effects:
     (Intr)
Days -0.184
> stopifnot(isTRUE(
+   all.equal(an1, an3)
+ ))
> (summary(fm, ddf="lme4"))
Linear mixed model fit by REML ['lmerMod']
Formula: Reaction ~ Days + (1 | Subject) + (0 + Days | Subject)
   Data: sleepstudy

REML criterion at convergence: 1743.7

Scaled residuals: 
    Min      1Q  Median      3Q     Max 
-3.9626 -0.4625  0.0204  0.4653  5.1860 

Random effects:
 Groups    Name        Variance Std.Dev.
 Subject   (Intercept) 627.57   25.051  
 Subject.1 Days         35.86    5.988  
 Residual              653.58   25.565  
Number of obs: 180, groups:  Subject, 18

Fixed effects:
            Estimate Std. Error t value
(Intercept)  251.405      6.885  36.513
Days          10.467      1.560   6.712

Correlation of Fixed Effects:
     (Intr)
Days -0.184
> if(has_pbkrtest) {
+   (summary(fm, ddf="Kenward-Roger"))
+   assertError(summary(fm, ddf="KR")) ## Error on incorrect arg.
+ }
> 
> ## lme4 method:
> an1 <- summary(fm, ddf="lme4")
> an2 <- summary(as(fm, "lmerMod"))
> stopifnot(isTRUE(
+   all.equal(an1, an2)
+ ))
> 
> 
> # Test printed output
> # - Satterthwaite
> x <- capture.output(sfm) # equal to output of 'print(sfm)'
> txt <- c("lmerModLmerTest", "t-tests use Satterthwaite's method",
+          "df", "t value", "Pr(>|t|)")
> stopifnot(all(
+   sapply(txt, function(text) any(grepl(text, x)))
+ ))
> 
> # Test printed output
> # - KR
> if(has_pbkrtest) {
+   (sfm <- summary(fm, ddf="Kenward-Roger"))
+   x <- capture.output(sfm)
+   txt <- c("lmerModLmerTest", "t-tests use Kenward-Roger's method",
+            "df", "t value", "Pr(>|t|)")
+   stopifnot(all(
+     sapply(txt, function(text) any(grepl(text, x)))
+   ))
+ }
> 
> ####################################
> ## Test 'boundary' fixef structures:
> ####################################
> 
> # Example with no fixef:
> m <- lmer(Reaction ~ -1 + (Days | Subject), sleepstudy)
> # m <- lmer(Reaction ~ 0 + (Days | Subject), sleepstudy) # alternative
> stopifnot(length(fixef(m)) == 0L)
> stopifnot(
+   nrow(coef(summary(m))) == 0L,
+   nrow(coef(summary(m, ddf="lme4"))) == 0L
+ )
> if(has_pbkrtest){
+   stopifnot(nrow(coef(summary(m, ddf="Kenward-Roger"))) == 0L)
+ }
> 
> # Example with intercept only:
> m <- lmer(Reaction ~ (Days | Subject), sleepstudy)
> # m <- lmer(Reaction ~ 1 + (Days | Subject), sleepstudy) # alternative
> stopifnot(length(fixef(m)) == 1L,
+           names(fixef(m)) == "(Intercept)")
> stopifnot(
+   nrow(coef(summary(m))) == 1L,
+   nrow(coef(summary(m, ddf="lme4"))) == 1L
+ )
> if(has_pbkrtest){
+   stopifnot(nrow(coef(summary(m, ddf="Kenward-Roger"))) == 1L)
+ }
> 
> # Example with >1 fixef without intercept:
> m <- lmer(Reaction ~ Days - 1 + I(Days^2) + (Days | Subject), sleepstudy)
> stopifnot(length(fixef(m)) == 2L,
+           names(fixef(m)) == c("Days", "I(Days^2)"))
> stopifnot(
+   nrow(coef(summary(m))) == 2L,
+   nrow(coef(summary(m, ddf="lme4"))) == 2L
+ )
> if(has_pbkrtest){
+   stopifnot(nrow(coef(summary(m, ddf="Kenward-Roger"))) == 2L)
+ }
> 
> 
> proc.time()
   user  system elapsed 
   3.53    0.21    3.73