R: Examples for 'pbkrtest::kr-modcomp'

### ** Examples


(fmLarge <- lmer(Reaction ~ Days + (Days|Subject), sleepstudy))

Linear mixed model fit by REML ['lmerMod']
Formula: Reaction ~ Days + (Days | Subject)
   Data: sleepstudy
REML criterion at convergence: 1743.628
Random effects:
 Groups   Name        Std.Dev. Corr
 Subject  (Intercept) 24.741       
          Days         5.922   0.07
 Residual             25.592       
Number of obs: 180, groups:  Subject, 18
Fixed Effects:
(Intercept)         Days  
     251.41        10.47

## removing Days
(fmSmall <- lmer(Reaction ~ 1 + (Days|Subject), sleepstudy))

Linear mixed model fit by REML ['lmerMod']
Formula: Reaction ~ 1 + (Days | Subject)
   Data: sleepstudy
REML criterion at convergence: 1769.845
Random effects:
 Groups   Name        Std.Dev. Corr 
 Subject  (Intercept) 25.53         
          Days        11.93    -0.18
 Residual             25.59         
Number of obs: 180, groups:  Subject, 18
Fixed Effects:
(Intercept)  
      257.8

anova(fmLarge,fmSmall)

refitting model(s) with ML (instead of REML)

Data: sleepstudy
Models:
fmSmall: Reaction ~ 1 + (Days | Subject)
fmLarge: Reaction ~ Days + (Days | Subject)
        npar    AIC    BIC  logLik deviance  Chisq Df Pr(>Chisq)    
fmSmall    5 1785.5 1801.4 -887.74   1775.5                         
fmLarge    6 1763.9 1783.1 -875.97   1751.9 23.537  1  1.226e-06 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

KRmodcomp(fmLarge,fmSmall)

large : Reaction ~ Days + (Days | Subject)
small : Reaction ~ 1 + (Days | Subject)
        stat    ndf    ddf F.scaling   p.value    
Ftest 45.853  1.000 17.000         1 3.264e-06 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

## The same test using a restriction matrix
L <- cbind(0,1)
KRmodcomp(fmLarge, L)

large : Reaction ~ Days + (Days | Subject)
L = 
     [,1] [,2]
[1,]    0    1
        stat    ndf    ddf F.scaling   p.value    
Ftest 45.853  1.000 17.000         1 3.264e-06 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

## Same example, but with independent intercept and slope effects:
m.large  <- lmer(Reaction ~ Days + (1|Subject) + (0+Days|Subject), data = sleepstudy)
m.small  <- lmer(Reaction ~ 1 + (1|Subject) + (0+Days|Subject), data = sleepstudy)
anova(m.large, m.small)

refitting model(s) with ML (instead of REML)

Data: sleepstudy
Models:
m.small: Reaction ~ 1 + (1 | Subject) + (0 + Days | Subject)
m.large: Reaction ~ Days + (1 | Subject) + (0 + Days | Subject)
        npar    AIC    BIC logLik deviance Chisq Df Pr(>Chisq)    
m.small    4 1783.6 1796.4 -887.8   1775.6                        
m.large    5 1762.0 1778.0 -876.0   1752.0  23.6  1  1.186e-06 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

KRmodcomp(m.large, m.small)

large : Reaction ~ Days + (1 | Subject) + (0 + Days | Subject)
small : Reaction ~ 1 + (1 | Subject) + (0 + Days | Subject)
        stat    ndf    ddf F.scaling   p.value    
Ftest 45.046  1.000 18.188         1 2.571e-06 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Examples for 'pbkrtest::kr-modcomp'

F-test and degrees of freedom based on Kenward-Roger approximation