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
