8 added 92 characters in body
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Update: After updating the contrasts based on @Henrik's answer:

> options(contrasts=c("contr.sum","contr.poly"))
> final.mod<-lmer(uV~1+factor(congruity)*factor(laterality)*factor(anteriority)+(1|sent.id)+(1|Subject),data=selected.data)
> summary(final.mod)
Linear mixed model fit by REML 
t-tests use  Satterthwaite approximations to degrees of freedom ['lmerMod']
Formula: uV ~ 1 + factor(congruity) * factor(laterality) *     factor(anteriority) +      (1 | sent.id) + (1 | Subject)
   Data: selected.data

REML criterion at convergence: 372689.8

Scaled residuals: 
    Min      1Q  Median      3Q     Max 
-9.6772 -0.5979 -0.0016  0.5977 12.3439 

Random effects:
 Groups   Name        Variance Std.Dev.
 sent.id  (Intercept)   5.556   2.357  
 Subject  (Intercept)   6.752   2.599  
 Residual             186.232  13.647  
Number of obs: 46176, groups:  sent.id, 41; Subject, 30

Fixed effects:
                                                              Estimate Std. Error         df t value Pr(>|t|)    
(Intercept)                                                  4.355e-01  6.039e-01  5.800e+01   0.721   0.4737    
factor(congruity)1                                           4.501e-01  6.396e-02  4.613e+04   7.037 1.99e-12 ***
factor(laterality)1                                          3.628e-01  8.983e-02  4.610e+04   4.039 5.38e-05 ***
factor(laterality)2                                         -5.732e-02  8.983e-02  4.610e+04  -0.638   0.5234    
factor(anteriority)1                                        -7.183e-01  6.352e-02  4.610e+04 -11.308  < 2e-16 ***
factor(congruity)1:factor(laterality)1                       1.433e-01  8.983e-02  4.610e+04   1.596   0.1106    
factor(congruity)1:factor(laterality)2                      -1.535e-01  8.983e-02  4.610e+04  -1.709   0.0875 .  
factor(congruity)1:factor(anteriority)1                      9.442e-02  6.352e-02  4.610e+04   1.487   0.1371    
factor(laterality)1:factor(anteriority)1                     2.282e-01  8.983e-02  4.610e+04   2.540   0.0111 *  
factor(laterality)2:factor(anteriority)1                    -2.121e-01  8.983e-02  4.610e+04  -2.362   0.0182 *  
factor(congruity)1:factor(laterality)1:factor(anteriority)1 -7.802e-03  8.983e-02  4.610e+04  -0.087   0.9308    
factor(congruity)1:factor(laterality)2:factor(anteriority)1 -1.141e-02  8.983e-02  4.610e+04  -0.127   0.8989    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Correlation of Fixed Effects:
                       (Intr) fctr(c)1 fctr(l)1 fct()2 fctr(n)1     fctr(cngrty)1:fctr(l)1 fc()1:()2 fctr(cngrty)1:fctr(n)1
fctr(cngr)1            -0.003                                                                                          
fctr(ltrl)1             0.000  0.000                                                                                   
fctr(ltrl)2             0.000  0.000   -0.500                                                                          
fctr(ntrr)1             0.000  0.000    0.000    0.000                                                                 
fctr(cngrty)1:fctr(l)1  0.000  0.000   -0.020    0.010  0.000                                                          
fctr()1:()2             0.000  0.000    0.010   -0.020  0.000   -0.500                                                 
fctr(cngrty)1:fctr(n)1  0.000  0.000    0.000    0.000 -0.020    0.000                  0.000                          
fctr(l)1:()1            0.000  0.000    0.000    0.000  0.000    0.000                  0.000     0.000                
fctr()2:()1             0.000  0.000    0.000    0.000  0.000    0.000                  0.000     0.000                
f()1:()1:()             0.000  0.000    0.000    0.000  0.000    0.000                  0.000     0.000                
f()1:()2:()             0.000  0.000    0.000    0.000  0.000    0.000                  0.000     0.000                
                       fctr(l)1:()1 f()2:( f()1:()1:
fctr(cngr)1                                         
fctr(ltrl)1                                         
fctr(ltrl)2                                         
fctr(ntrr)1                                         
fctr(cngrty)1:fctr(l)1                              
fctr()1:()2                                         
fctr(cngrty)1:fctr(n)1                              
fctr(l)1:()1                                        
fctr()2:()1            -0.500                       
f()1:()1:()            -0.020        0.010          
f()1:()2:()             0.010       -0.020 -0.500   
> anova(final.mod)
Analysis of Variance Table of type III  with  Satterthwaite 
approximation for degrees of freedom
                                                          Sum Sq Mean Sq NumDF DenDF F.value    Pr(>F)    
factor(congruity)                                         9221.9  9221.9     1 46129  49.518 1.993e-12 ***
factor(laterality)                                        3511.5  1755.7     2 46095   9.428 8.062e-05 ***
factor(anteriority)                                      23814.0 23814.0     1 46095 127.873 < 2.2e-16 ***
factor(congruity):factor(laterality)                       680.3   340.1     2 46095   1.826   0.16101    
factor(congruity):factor(anteriority)                      411.5   411.5     1 46095   2.210   0.13714    
factor(laterality):factor(anteriority)                    1497.4   748.7     2 46095   4.020   0.01796 *  
factor(congruity):factor(laterality):factor(anteriority)     8.6     4.3     2 46095   0.023   0.97713    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

After updating the contrasts:

> final.mod<-lmer(uV~1+factor(congruity)*factor(laterality)*factor(anteriority)+(1|sent.id)+(1|Subject),data=selected.data)
> summary(final.mod)
Linear mixed model fit by REML 
t-tests use  Satterthwaite approximations to degrees of freedom ['lmerMod']
Formula: uV ~ 1 + factor(congruity) * factor(laterality) *     factor(anteriority) +      (1 | sent.id) + (1 | Subject)
   Data: selected.data

REML criterion at convergence: 372689.8

Scaled residuals: 
    Min      1Q  Median      3Q     Max 
-9.6772 -0.5979 -0.0016  0.5977 12.3439 

Random effects:
 Groups   Name        Variance Std.Dev.
 sent.id  (Intercept)   5.556   2.357  
 Subject  (Intercept)   6.752   2.599  
 Residual             186.232  13.647  
Number of obs: 46176, groups:  sent.id, 41; Subject, 30

Fixed effects:
                                                              Estimate Std. Error         df t value Pr(>|t|)    
(Intercept)                                                  4.355e-01  6.039e-01  5.800e+01   0.721   0.4737    
factor(congruity)1                                           4.501e-01  6.396e-02  4.613e+04   7.037 1.99e-12 ***
factor(laterality)1                                          3.628e-01  8.983e-02  4.610e+04   4.039 5.38e-05 ***
factor(laterality)2                                         -5.732e-02  8.983e-02  4.610e+04  -0.638   0.5234    
factor(anteriority)1                                        -7.183e-01  6.352e-02  4.610e+04 -11.308  < 2e-16 ***
factor(congruity)1:factor(laterality)1                       1.433e-01  8.983e-02  4.610e+04   1.596   0.1106    
factor(congruity)1:factor(laterality)2                      -1.535e-01  8.983e-02  4.610e+04  -1.709   0.0875 .  
factor(congruity)1:factor(anteriority)1                      9.442e-02  6.352e-02  4.610e+04   1.487   0.1371    
factor(laterality)1:factor(anteriority)1                     2.282e-01  8.983e-02  4.610e+04   2.540   0.0111 *  
factor(laterality)2:factor(anteriority)1                    -2.121e-01  8.983e-02  4.610e+04  -2.362   0.0182 *  
factor(congruity)1:factor(laterality)1:factor(anteriority)1 -7.802e-03  8.983e-02  4.610e+04  -0.087   0.9308    
factor(congruity)1:factor(laterality)2:factor(anteriority)1 -1.141e-02  8.983e-02  4.610e+04  -0.127   0.8989    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Correlation of Fixed Effects:
                       (Intr) fctr(c)1 fctr(l)1 fct()2 fctr(n)1     fctr(cngrty)1:fctr(l)1 fc()1:()2 fctr(cngrty)1:fctr(n)1
fctr(cngr)1            -0.003                                                                                          
fctr(ltrl)1             0.000  0.000                                                                                   
fctr(ltrl)2             0.000  0.000   -0.500                                                                          
fctr(ntrr)1             0.000  0.000    0.000    0.000                                                                 
fctr(cngrty)1:fctr(l)1  0.000  0.000   -0.020    0.010  0.000                                                          
fctr()1:()2             0.000  0.000    0.010   -0.020  0.000   -0.500                                                 
fctr(cngrty)1:fctr(n)1  0.000  0.000    0.000    0.000 -0.020    0.000                  0.000                          
fctr(l)1:()1            0.000  0.000    0.000    0.000  0.000    0.000                  0.000     0.000                
fctr()2:()1             0.000  0.000    0.000    0.000  0.000    0.000                  0.000     0.000                
f()1:()1:()             0.000  0.000    0.000    0.000  0.000    0.000                  0.000     0.000                
f()1:()2:()             0.000  0.000    0.000    0.000  0.000    0.000                  0.000     0.000                
                       fctr(l)1:()1 f()2:( f()1:()1:
fctr(cngr)1                                         
fctr(ltrl)1                                         
fctr(ltrl)2                                         
fctr(ntrr)1                                         
fctr(cngrty)1:fctr(l)1                              
fctr()1:()2                                         
fctr(cngrty)1:fctr(n)1                              
fctr(l)1:()1                                        
fctr()2:()1            -0.500                       
f()1:()1:()            -0.020        0.010          
f()1:()2:()             0.010       -0.020 -0.500   
> anova(final.mod)
Analysis of Variance Table of type III  with  Satterthwaite 
approximation for degrees of freedom
                                                          Sum Sq Mean Sq NumDF DenDF F.value    Pr(>F)    
factor(congruity)                                         9221.9  9221.9     1 46129  49.518 1.993e-12 ***
factor(laterality)                                        3511.5  1755.7     2 46095   9.428 8.062e-05 ***
factor(anteriority)                                      23814.0 23814.0     1 46095 127.873 < 2.2e-16 ***
factor(congruity):factor(laterality)                       680.3   340.1     2 46095   1.826   0.16101    
factor(congruity):factor(anteriority)                      411.5   411.5     1 46095   2.210   0.13714    
factor(laterality):factor(anteriority)                    1497.4   748.7     2 46095   4.020   0.01796 *  
factor(congruity):factor(laterality):factor(anteriority)     8.6     4.3     2 46095   0.023   0.97713    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Update: After updating the contrasts based on @Henrik's answer:

> options(contrasts=c("contr.sum","contr.poly"))
> final.mod<-lmer(uV~1+factor(congruity)*factor(laterality)*factor(anteriority)+(1|sent.id)+(1|Subject),data=selected.data)
> summary(final.mod)
Linear mixed model fit by REML 
t-tests use  Satterthwaite approximations to degrees of freedom ['lmerMod']
Formula: uV ~ 1 + factor(congruity) * factor(laterality) *     factor(anteriority) +      (1 | sent.id) + (1 | Subject)
   Data: selected.data

REML criterion at convergence: 372689.8

Scaled residuals: 
    Min      1Q  Median      3Q     Max 
-9.6772 -0.5979 -0.0016  0.5977 12.3439 

Random effects:
 Groups   Name        Variance Std.Dev.
 sent.id  (Intercept)   5.556   2.357  
 Subject  (Intercept)   6.752   2.599  
 Residual             186.232  13.647  
Number of obs: 46176, groups:  sent.id, 41; Subject, 30

Fixed effects:
                                                              Estimate Std. Error         df t value Pr(>|t|)    
(Intercept)                                                  4.355e-01  6.039e-01  5.800e+01   0.721   0.4737    
factor(congruity)1                                           4.501e-01  6.396e-02  4.613e+04   7.037 1.99e-12 ***
factor(laterality)1                                          3.628e-01  8.983e-02  4.610e+04   4.039 5.38e-05 ***
factor(laterality)2                                         -5.732e-02  8.983e-02  4.610e+04  -0.638   0.5234    
factor(anteriority)1                                        -7.183e-01  6.352e-02  4.610e+04 -11.308  < 2e-16 ***
factor(congruity)1:factor(laterality)1                       1.433e-01  8.983e-02  4.610e+04   1.596   0.1106    
factor(congruity)1:factor(laterality)2                      -1.535e-01  8.983e-02  4.610e+04  -1.709   0.0875 .  
factor(congruity)1:factor(anteriority)1                      9.442e-02  6.352e-02  4.610e+04   1.487   0.1371    
factor(laterality)1:factor(anteriority)1                     2.282e-01  8.983e-02  4.610e+04   2.540   0.0111 *  
factor(laterality)2:factor(anteriority)1                    -2.121e-01  8.983e-02  4.610e+04  -2.362   0.0182 *  
factor(congruity)1:factor(laterality)1:factor(anteriority)1 -7.802e-03  8.983e-02  4.610e+04  -0.087   0.9308    
factor(congruity)1:factor(laterality)2:factor(anteriority)1 -1.141e-02  8.983e-02  4.610e+04  -0.127   0.8989    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Correlation of Fixed Effects:
                       (Intr) fctr(c)1 fctr(l)1 fct()2 fctr(n)1     fctr(cngrty)1:fctr(l)1 fc()1:()2 fctr(cngrty)1:fctr(n)1
fctr(cngr)1            -0.003                                                                                          
fctr(ltrl)1             0.000  0.000                                                                                   
fctr(ltrl)2             0.000  0.000   -0.500                                                                          
fctr(ntrr)1             0.000  0.000    0.000    0.000                                                                 
fctr(cngrty)1:fctr(l)1  0.000  0.000   -0.020    0.010  0.000                                                          
fctr()1:()2             0.000  0.000    0.010   -0.020  0.000   -0.500                                                 
fctr(cngrty)1:fctr(n)1  0.000  0.000    0.000    0.000 -0.020    0.000                  0.000                          
fctr(l)1:()1            0.000  0.000    0.000    0.000  0.000    0.000                  0.000     0.000                
fctr()2:()1             0.000  0.000    0.000    0.000  0.000    0.000                  0.000     0.000                
f()1:()1:()             0.000  0.000    0.000    0.000  0.000    0.000                  0.000     0.000                
f()1:()2:()             0.000  0.000    0.000    0.000  0.000    0.000                  0.000     0.000                
                       fctr(l)1:()1 f()2:( f()1:()1:
fctr(cngr)1                                         
fctr(ltrl)1                                         
fctr(ltrl)2                                         
fctr(ntrr)1                                         
fctr(cngrty)1:fctr(l)1                              
fctr()1:()2                                         
fctr(cngrty)1:fctr(n)1                              
fctr(l)1:()1                                        
fctr()2:()1            -0.500                       
f()1:()1:()            -0.020        0.010          
f()1:()2:()             0.010       -0.020 -0.500   
> anova(final.mod)
Analysis of Variance Table of type III  with  Satterthwaite 
approximation for degrees of freedom
                                                          Sum Sq Mean Sq NumDF DenDF F.value    Pr(>F)    
factor(congruity)                                         9221.9  9221.9     1 46129  49.518 1.993e-12 ***
factor(laterality)                                        3511.5  1755.7     2 46095   9.428 8.062e-05 ***
factor(anteriority)                                      23814.0 23814.0     1 46095 127.873 < 2.2e-16 ***
factor(congruity):factor(laterality)                       680.3   340.1     2 46095   1.826   0.16101    
factor(congruity):factor(anteriority)                      411.5   411.5     1 46095   2.210   0.13714    
factor(laterality):factor(anteriority)                    1497.4   748.7     2 46095   4.020   0.01796 *  
factor(congruity):factor(laterality):factor(anteriority)     8.6     4.3     2 46095   0.023   0.97713    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
    Notice removed Draw attention by Ishisht
    Bounty Ended with Henrik's answer chosen by Ishisht
7 added 5894 characters in body
source | link

After updating the contrasts:

> final.mod<-lmer(uV~1+factor(congruity)*factor(laterality)*factor(anteriority)+(1|sent.id)+(1|Subject),data=selected.data)
> summary(final.mod)
Linear mixed model fit by REML 
t-tests use  Satterthwaite approximations to degrees of freedom ['lmerMod']
Formula: uV ~ 1 + factor(congruity) * factor(laterality) *     factor(anteriority) +      (1 | sent.id) + (1 | Subject)
   Data: selected.data

REML criterion at convergence: 372689.8

Scaled residuals: 
    Min      1Q  Median      3Q     Max 
-9.6772 -0.5979 -0.0016  0.5977 12.3439 

Random effects:
 Groups   Name        Variance Std.Dev.
 sent.id  (Intercept)   5.556   2.357  
 Subject  (Intercept)   6.752   2.599  
 Residual             186.232  13.647  
Number of obs: 46176, groups:  sent.id, 41; Subject, 30

Fixed effects:
                                                              Estimate Std. Error         df t value Pr(>|t|)    
(Intercept)                                                  4.355e-01  6.039e-01  5.800e+01   0.721   0.4737    
factor(congruity)1                                           4.501e-01  6.396e-02  4.613e+04   7.037 1.99e-12 ***
factor(laterality)1                                          3.628e-01  8.983e-02  4.610e+04   4.039 5.38e-05 ***
factor(laterality)2                                         -5.732e-02  8.983e-02  4.610e+04  -0.638   0.5234    
factor(anteriority)1                                        -7.183e-01  6.352e-02  4.610e+04 -11.308  < 2e-16 ***
factor(congruity)1:factor(laterality)1                       1.433e-01  8.983e-02  4.610e+04   1.596   0.1106    
factor(congruity)1:factor(laterality)2                      -1.535e-01  8.983e-02  4.610e+04  -1.709   0.0875 .  
factor(congruity)1:factor(anteriority)1                      9.442e-02  6.352e-02  4.610e+04   1.487   0.1371    
factor(laterality)1:factor(anteriority)1                     2.282e-01  8.983e-02  4.610e+04   2.540   0.0111 *  
factor(laterality)2:factor(anteriority)1                    -2.121e-01  8.983e-02  4.610e+04  -2.362   0.0182 *  
factor(congruity)1:factor(laterality)1:factor(anteriority)1 -7.802e-03  8.983e-02  4.610e+04  -0.087   0.9308    
factor(congruity)1:factor(laterality)2:factor(anteriority)1 -1.141e-02  8.983e-02  4.610e+04  -0.127   0.8989    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Correlation of Fixed Effects:
                       (Intr) fctr(c)1 fctr(l)1 fct()2 fctr(n)1     fctr(cngrty)1:fctr(l)1 fc()1:()2 fctr(cngrty)1:fctr(n)1
fctr(cngr)1            -0.003                                                                                          
fctr(ltrl)1             0.000  0.000                                                                                   
fctr(ltrl)2             0.000  0.000   -0.500                                                                          
fctr(ntrr)1             0.000  0.000    0.000    0.000                                                                 
fctr(cngrty)1:fctr(l)1  0.000  0.000   -0.020    0.010  0.000                                                          
fctr()1:()2             0.000  0.000    0.010   -0.020  0.000   -0.500                                                 
fctr(cngrty)1:fctr(n)1  0.000  0.000    0.000    0.000 -0.020    0.000                  0.000                          
fctr(l)1:()1            0.000  0.000    0.000    0.000  0.000    0.000                  0.000     0.000                
fctr()2:()1             0.000  0.000    0.000    0.000  0.000    0.000                  0.000     0.000                
f()1:()1:()             0.000  0.000    0.000    0.000  0.000    0.000                  0.000     0.000                
f()1:()2:()             0.000  0.000    0.000    0.000  0.000    0.000                  0.000     0.000                
                       fctr(l)1:()1 f()2:( f()1:()1:
fctr(cngr)1                                         
fctr(ltrl)1                                         
fctr(ltrl)2                                         
fctr(ntrr)1                                         
fctr(cngrty)1:fctr(l)1                              
fctr()1:()2                                         
fctr(cngrty)1:fctr(n)1                              
fctr(l)1:()1                                        
fctr()2:()1            -0.500                       
f()1:()1:()            -0.020        0.010          
f()1:()2:()             0.010       -0.020 -0.500   
> anova(final.mod)
Analysis of Variance Table of type III  with  Satterthwaite 
approximation for degrees of freedom
                                                          Sum Sq Mean Sq NumDF DenDF F.value    Pr(>F)    
factor(congruity)                                         9221.9  9221.9     1 46129  49.518 1.993e-12 ***
factor(laterality)                                        3511.5  1755.7     2 46095   9.428 8.062e-05 ***
factor(anteriority)                                      23814.0 23814.0     1 46095 127.873 < 2.2e-16 ***
factor(congruity):factor(laterality)                       680.3   340.1     2 46095   1.826   0.16101    
factor(congruity):factor(anteriority)                      411.5   411.5     1 46095   2.210   0.13714    
factor(laterality):factor(anteriority)                    1497.4   748.7     2 46095   4.020   0.01796 *  
factor(congruity):factor(laterality):factor(anteriority)     8.6     4.3     2 46095   0.023   0.97713    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

After updating the contrasts:

> final.mod<-lmer(uV~1+factor(congruity)*factor(laterality)*factor(anteriority)+(1|sent.id)+(1|Subject),data=selected.data)
> summary(final.mod)
Linear mixed model fit by REML 
t-tests use  Satterthwaite approximations to degrees of freedom ['lmerMod']
Formula: uV ~ 1 + factor(congruity) * factor(laterality) *     factor(anteriority) +      (1 | sent.id) + (1 | Subject)
   Data: selected.data

REML criterion at convergence: 372689.8

Scaled residuals: 
    Min      1Q  Median      3Q     Max 
-9.6772 -0.5979 -0.0016  0.5977 12.3439 

Random effects:
 Groups   Name        Variance Std.Dev.
 sent.id  (Intercept)   5.556   2.357  
 Subject  (Intercept)   6.752   2.599  
 Residual             186.232  13.647  
Number of obs: 46176, groups:  sent.id, 41; Subject, 30

Fixed effects:
                                                              Estimate Std. Error         df t value Pr(>|t|)    
(Intercept)                                                  4.355e-01  6.039e-01  5.800e+01   0.721   0.4737    
factor(congruity)1                                           4.501e-01  6.396e-02  4.613e+04   7.037 1.99e-12 ***
factor(laterality)1                                          3.628e-01  8.983e-02  4.610e+04   4.039 5.38e-05 ***
factor(laterality)2                                         -5.732e-02  8.983e-02  4.610e+04  -0.638   0.5234    
factor(anteriority)1                                        -7.183e-01  6.352e-02  4.610e+04 -11.308  < 2e-16 ***
factor(congruity)1:factor(laterality)1                       1.433e-01  8.983e-02  4.610e+04   1.596   0.1106    
factor(congruity)1:factor(laterality)2                      -1.535e-01  8.983e-02  4.610e+04  -1.709   0.0875 .  
factor(congruity)1:factor(anteriority)1                      9.442e-02  6.352e-02  4.610e+04   1.487   0.1371    
factor(laterality)1:factor(anteriority)1                     2.282e-01  8.983e-02  4.610e+04   2.540   0.0111 *  
factor(laterality)2:factor(anteriority)1                    -2.121e-01  8.983e-02  4.610e+04  -2.362   0.0182 *  
factor(congruity)1:factor(laterality)1:factor(anteriority)1 -7.802e-03  8.983e-02  4.610e+04  -0.087   0.9308    
factor(congruity)1:factor(laterality)2:factor(anteriority)1 -1.141e-02  8.983e-02  4.610e+04  -0.127   0.8989    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Correlation of Fixed Effects:
                       (Intr) fctr(c)1 fctr(l)1 fct()2 fctr(n)1     fctr(cngrty)1:fctr(l)1 fc()1:()2 fctr(cngrty)1:fctr(n)1
fctr(cngr)1            -0.003                                                                                          
fctr(ltrl)1             0.000  0.000                                                                                   
fctr(ltrl)2             0.000  0.000   -0.500                                                                          
fctr(ntrr)1             0.000  0.000    0.000    0.000                                                                 
fctr(cngrty)1:fctr(l)1  0.000  0.000   -0.020    0.010  0.000                                                          
fctr()1:()2             0.000  0.000    0.010   -0.020  0.000   -0.500                                                 
fctr(cngrty)1:fctr(n)1  0.000  0.000    0.000    0.000 -0.020    0.000                  0.000                          
fctr(l)1:()1            0.000  0.000    0.000    0.000  0.000    0.000                  0.000     0.000                
fctr()2:()1             0.000  0.000    0.000    0.000  0.000    0.000                  0.000     0.000                
f()1:()1:()             0.000  0.000    0.000    0.000  0.000    0.000                  0.000     0.000                
f()1:()2:()             0.000  0.000    0.000    0.000  0.000    0.000                  0.000     0.000                
                       fctr(l)1:()1 f()2:( f()1:()1:
fctr(cngr)1                                         
fctr(ltrl)1                                         
fctr(ltrl)2                                         
fctr(ntrr)1                                         
fctr(cngrty)1:fctr(l)1                              
fctr()1:()2                                         
fctr(cngrty)1:fctr(n)1                              
fctr(l)1:()1                                        
fctr()2:()1            -0.500                       
f()1:()1:()            -0.020        0.010          
f()1:()2:()             0.010       -0.020 -0.500   
> anova(final.mod)
Analysis of Variance Table of type III  with  Satterthwaite 
approximation for degrees of freedom
                                                          Sum Sq Mean Sq NumDF DenDF F.value    Pr(>F)    
factor(congruity)                                         9221.9  9221.9     1 46129  49.518 1.993e-12 ***
factor(laterality)                                        3511.5  1755.7     2 46095   9.428 8.062e-05 ***
factor(anteriority)                                      23814.0 23814.0     1 46095 127.873 < 2.2e-16 ***
factor(congruity):factor(laterality)                       680.3   340.1     2 46095   1.826   0.16101    
factor(congruity):factor(anteriority)                      411.5   411.5     1 46095   2.210   0.13714    
factor(laterality):factor(anteriority)                    1497.4   748.7     2 46095   4.020   0.01796 *  
factor(congruity):factor(laterality):factor(anteriority)     8.6     4.3     2 46095   0.023   0.97713    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
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Big difference between a t-test and a F-test in a mixed model (anova vs summary for lmer/lmerModin lmerTest)

While helping someone else with their analyses, I've run into a question regarding the difference between t-tests and F-tests for linear mixed models in lme4 for R, as provided by lmerModlmerTest. I'm aware of the problems with calculating any kind of p-values for linear mixed models (as I understand, primarily due to the fact that definition of the degrees of freedom is problematic), as well as the problems with interpreting main effects in the presence of significant interactions (based on the marginality principle).

Big difference between a t-test and a F-test in a mixed model (anova vs summary for lmer/lmerMod)

While helping someone else with their analyses, I've run into a question regarding the difference between t-tests and F-tests for linear mixed models in lme4 for R, as provided by lmerMod. I'm aware of the problems with calculating any kind of p-values for linear mixed models (as I understand, primarily due to the fact that definition of the degrees of freedom is problematic), as well as the problems with interpreting main effects in the presence of significant interactions (based on the marginality principle).

Big difference between a t-test and a F-test in a mixed model (anova vs summary in lmerTest)

While helping someone else with their analyses, I've run into a question regarding the difference between t-tests and F-tests for linear mixed models in lme4 for R, as provided by lmerTest. I'm aware of the problems with calculating any kind of p-values for linear mixed models (as I understand, primarily due to the fact that definition of the degrees of freedom is problematic), as well as the problems with interpreting main effects in the presence of significant interactions (based on the marginality principle).

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