[1] "[SFD]"
Linear mixed model fit by maximum likelihood 
Formula: log(SFD) ~ scale(log_freq, scale = F) + scale(len, scale = F) +      scale(bigram, scale = F) + scale(logitpred, scale = F) +      (1 | sn) + (1 | id) 
   Data: d.sfd 
   AIC   BIC logLik deviance REMLdev
 43224 43300 -21604    43208   43267
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0150452 0.122659
 sn       (Intercept) 0.0012718 0.035662
 Residual             0.0887098 0.297842
Number of obs: 100860, groups: id, 222; sn, 144

Fixed effects:
                              Estimate Std. Error t value
(Intercept)                  5.2749093  0.0088086   598.8
scale(log_freq, scale = F)  -0.0024826  0.0011574    -2.1
scale(len, scale = F)        0.0057546  0.0005690    10.1
scale(bigram, scale = F)    -0.0126764  0.0004116   -30.8
scale(logitpred, scale = F) -0.0063591  0.0011285    -5.6

Correlation of Fixed Effects:
            (Intr) s(_s=F scl(ln,s=F) scl(b,s=F)
scl(l_,s=F) -0.002                              
scl(ln,s=F) -0.002  0.565                       
scl(bg,s=F)  0.004 -0.287 -0.067                
scl(lg,s=F)  0.001 -0.288  0.078      -0.240    
Linear mixed model fit by maximum likelihood 
Formula: log(SFD) ~ scale(log_freq, scale = F) + scale(len, scale = F) +      scale(bigram, scale = F) + scale(logitpred, scale = F) +      scale(surprisalDep, scale = F) + (1 | sn) + (1 | id) 
   Data: d.sfd 
   AIC   BIC logLik deviance REMLdev
 42803 42889 -21393    42785   42855
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0150463 0.122663
 sn       (Intercept) 0.0014192 0.037672
 Residual             0.0883250 0.297195
Number of obs: 100860, groups: id, 222; sn, 144

Fixed effects:
                                 Estimate Std. Error t value
(Intercept)                     5.2760016  0.0088666   595.0
scale(log_freq, scale = F)     -0.0000386  0.0011620 -0.0332
scale(len, scale = F)           0.0060119  0.0005687    10.6
scale(bigram, scale = F)       -0.0131375  0.0004117   -31.9
scale(logitpred, scale = F)    -0.0126932  0.0011681   -10.9
scale(surprisalDep, scale = F)  0.0327203  0.0015886    20.6

Correlation of Fixed Effects:
            (Intr) s(_s=F scl(ln,s=F) scl(b,s=F) scl(lg,s=F)
scl(l_,s=F) -0.001                                          
scl(ln,s=F) -0.002  0.565                                   
scl(bg,s=F)  0.004 -0.291 -0.068                            
scl(lg,s=F)  0.000 -0.304  0.068      -0.217                
scl(sD,s=F)  0.006  0.102  0.023      -0.056     -0.263     
Linear mixed model fit by maximum likelihood 
Formula: log(SFD) ~ scale(log_freq, scale = F) + scale(len, scale = F) +      scale(bigram, scale = F) + scale(logitpred, scale = F) +      scale(time, scale = F) + (1 | sn) + (1 | id) 
   Data: d.sfd 
   AIC   BIC logLik deviance REMLdev
 43216 43302 -21599    43198   43278
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0150387 0.122632
 sn       (Intercept) 0.0012741 0.035695
 Residual             0.0887008 0.297827
Number of obs: 100860, groups: id, 222; sn, 144

Fixed effects:
                              Estimate Std. Error t value
(Intercept)                  5.275e+00  8.808e-03   598.9
scale(log_freq, scale = F)  -1.585e-03  1.192e-03    -1.3
scale(len, scale = F)        5.921e-03  5.714e-04    10.4
scale(bigram, scale = F)    -1.260e-02  4.122e-04   -30.6
scale(logitpred, scale = F) -6.644e-03  1.132e-03    -5.9
scale(time, scale = F)       3.507e-05  1.110e-05     3.2

Correlation of Fixed Effects:
            (Intr) s(_s=F scl(ln,s=F) scl(b,s=F) scl(lg,s=F)
scl(l_,s=F) -0.002                                          
scl(ln,s=F) -0.002  0.568                                   
scl(bg,s=F)  0.004 -0.265 -0.061                            
scl(lg,s=F)  0.001 -0.298  0.070      -0.244                
scl(tm,s=F)  0.000  0.238  0.093       0.056     -0.080     
Linear mixed model fit by maximum likelihood 
Formula: log(SFD) ~ scale(log_freq, scale = F) + scale(len, scale = F) +      scale(bigram, scale = F) + scale(logitpred, scale = F) +      scale(surprisalDep, scale = F) + scale(time, scale = F) +      (1 | sn) + (1 | id) 
   Data: d.sfd 
   AIC   BIC logLik deviance REMLdev
 42781 42876 -21381    42761   42852
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0150360 0.12262 
 sn       (Intercept) 0.0014168 0.03764 
 Residual             0.0883042 0.29716 
Number of obs: 100860, groups: id, 222; sn, 144

Fixed effects:
                                 Estimate Std. Error t value
(Intercept)                     5.276e+00  8.863e-03   595.3
scale(log_freq, scale = F)      1.405e-03  1.199e-03     1.2
scale(len, scale = F)           6.277e-03  5.712e-04    11.0
scale(bigram, scale = F)       -1.303e-02  4.122e-04   -31.6
scale(logitpred, scale = F)    -1.326e-02  1.174e-03   -11.3
scale(surprisalDep, scale = F)  3.337e-02  1.594e-03    20.9
scale(time, scale = F)          5.452e-05  1.112e-05     4.9

Correlation of Fixed Effects:
            (Intr) s(_s=F scl(ln,s=F) scl(b,s=F) scl(lg,s=F) s(Ds=F
scl(l_,s=F) -0.001                                                 
scl(ln,s=F) -0.002  0.568                                          
scl(bg,s=F)  0.004 -0.269 -0.063                                   
scl(lg,s=F) -0.001 -0.317  0.058      -0.221                       
scl(sD,s=F)  0.006  0.119  0.031      -0.051     -0.269            
scl(tm,s=F)  0.000  0.246  0.095       0.052     -0.099       0.083
[1] "[FFD]"
Linear mixed model fit by maximum likelihood 
Formula: log(FFD) ~ scale(log_freq, scale = F) + scale(len, scale = F) +      scale(bigram, scale = F) + scale(logitpred, scale = F) +      (1 | sn) + (1 | id) 
   Data: d.ffd 
   AIC   BIC logLik deviance REMLdev
 52546 52624 -26265    52530   52590
Random effects:
 Groups   Name        Variance   Std.Dev.
 id       (Intercept) 0.01437042 0.119877
 sn       (Intercept) 0.00099277 0.031508
 Residual             0.08783774 0.296374
Number of obs: 126198, groups: id, 222; sn, 144

Fixed effects:
                              Estimate Std. Error t value
(Intercept)                  5.2717863  0.0085079   619.6
scale(log_freq, scale = F)   0.0017730  0.0010420     1.7
scale(len, scale = F)       -0.0021263  0.0004431    -4.8
scale(bigram, scale = F)    -0.0132049  0.0003811   -34.6
scale(logitpred, scale = F) -0.0015712  0.0010359    -1.5

Correlation of Fixed Effects:
            (Intr) s(_s=F scl(ln,s=F) scl(b,s=F)
scl(l_,s=F)  0.000                              
scl(ln,s=F) -0.001  0.548                       
scl(bg,s=F)  0.001 -0.309 -0.071                
scl(lg,s=F)  0.001 -0.295  0.065      -0.246    
Linear mixed model fit by maximum likelihood 
Formula: log(FFD) ~ scale(log_freq, scale = F) + scale(len, scale = F) +      scale(bigram, scale = F) + scale(logitpred, scale = F) +      scale(surprisalDep, scale = F) + (1 | sn) + (1 | id) 
   Data: d.ffd 
   AIC   BIC logLik deviance REMLdev
 51695 51783 -25838    51677   51748
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0143775 0.119906
 sn       (Intercept) 0.0012159 0.034869
 Residual             0.0872256 0.295340
Number of obs: 126198, groups: id, 222; sn, 144

Fixed effects:
                                 Estimate Std. Error t value
(Intercept)                     5.2729575  0.0086001   613.1
scale(log_freq, scale = F)      0.0052230  0.0010468     5.0
scale(len, scale = F)          -0.0019671  0.0004428    -4.4
scale(bigram, scale = F)       -0.0138679  0.0003812   -36.4
scale(logitpred, scale = F)    -0.0104199  0.0010770    -9.7
scale(surprisalDep, scale = F)  0.0416810  0.0014223    29.3

Correlation of Fixed Effects:
            (Intr) s(_s=F scl(ln,s=F) scl(b,s=F) scl(lg,s=F)
scl(l_,s=F)  0.000                                          
scl(ln,s=F) -0.001  0.547                                   
scl(bg,s=F)  0.001 -0.313 -0.072                            
scl(lg,s=F)  0.000 -0.313  0.058      -0.219                
scl(sD,s=F)  0.005  0.112  0.015      -0.062     -0.280     
Linear mixed model fit by maximum likelihood 
Formula: log(FFD) ~ scale(log_freq, scale = F) + scale(len, scale = F) +      scale(bigram, scale = F) + scale(logitpred, scale = F) +      scale(time, scale = F) + (1 | sn) + (1 | id) 
   Data: d.ffd 
   AIC   BIC logLik deviance REMLdev
 52543 52631 -26263    52525   52606
Random effects:
 Groups   Name        Variance   Std.Dev.
 id       (Intercept) 0.01436831 0.119868
 sn       (Intercept) 0.00099313 0.031514
 Residual             0.08783406 0.296368
Number of obs: 126198, groups: id, 222; sn, 144

Fixed effects:
                              Estimate Std. Error t value
(Intercept)                  5.272e+00  8.507e-03   619.7
scale(log_freq, scale = F)   2.317e-03  1.069e-03     2.2
scale(len, scale = F)       -2.008e-03  4.461e-04    -4.5
scale(bigram, scale = F)    -1.315e-02  3.819e-04   -34.4
scale(logitpred, scale = F) -1.777e-03  1.040e-03    -1.7
scale(time, scale = F)       2.244e-05  9.792e-06     2.3

Correlation of Fixed Effects:
            (Intr) s(_s=F scl(ln,s=F) scl(b,s=F) scl(lg,s=F)
scl(l_,s=F)  0.000                                          
scl(ln,s=F) -0.001  0.557                                   
scl(bg,s=F)  0.001 -0.287 -0.063                            
scl(lg,s=F)  0.001 -0.306  0.055      -0.250                
scl(tm,s=F) -0.001  0.222  0.116       0.063     -0.086     
Linear mixed model fit by maximum likelihood 
Formula: log(FFD) ~ scale(log_freq, scale = F) + scale(len, scale = F) +      scale(bigram, scale = F) + scale(logitpred, scale = F) +      scale(surprisalDep, scale = F) + scale(time, scale = F) +      (1 | sn) + (1 | id) 
   Data: d.ffd 
   AIC   BIC logLik deviance REMLdev
 51676 51773 -25828    51656   51748
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0143734 0.119889
 sn       (Intercept) 0.0012098 0.034782
 Residual             0.0872116 0.295316
Number of obs: 126198, groups: id, 222; sn, 144

Fixed effects:
                                 Estimate Std. Error t value
(Intercept)                     5.273e+00  8.597e-03   613.4
scale(log_freq, scale = F)      6.352e-03  1.075e-03     5.9
scale(len, scale = F)          -1.727e-03  4.458e-04    -3.9
scale(bigram, scale = F)       -1.377e-02  3.818e-04   -36.1
scale(logitpred, scale = F)    -1.094e-02  1.083e-03   -10.1
scale(surprisalDep, scale = F)  4.218e-02  1.426e-03    29.6
scale(time, scale = F)          4.480e-05  9.801e-06     4.6

Correlation of Fixed Effects:
            (Intr) s(_s=F scl(ln,s=F) scl(b,s=F) scl(lg,s=F) s(Ds=F
scl(l_,s=F)  0.000                                                 
scl(ln,s=F) -0.001  0.556                                          
scl(bg,s=F)  0.001 -0.291 -0.065                                   
scl(lg,s=F)  0.000 -0.327  0.045      -0.224                       
scl(sD,s=F)  0.005  0.127  0.024      -0.057     -0.286            
scl(tm,s=F)  0.000  0.230  0.117       0.059     -0.105       0.077
[1] "[RPD]"
Linear mixed model fit by maximum likelihood 
Formula: log(RPD) ~ scale(log_freq, scale = F) + scale(len, scale = F) +      scale(bigram, scale = F) + scale(logitpred, scale = F) +      (1 | sn) + (1 | id) 
   Data: d.rpd 
    AIC    BIC logLik deviance REMLdev
 157700 157779 -78842   157684  157740
Random effects:
 Groups   Name        Variance Std.Dev.
 id       (Intercept) 0.031156 0.176509
 sn       (Intercept) 0.004976 0.070541
 Residual             0.185775 0.431016
Number of obs: 135274, groups: id, 222; sn, 144

Fixed effects:
                              Estimate Std. Error t value
(Intercept)                  5.4709308  0.0132807   411.9
scale(log_freq, scale = F)  -0.0078903  0.0014564    -5.4
scale(len, scale = F)        0.0357236  0.0006320    56.5
scale(bigram, scale = F)    -0.0076166  0.0005318   -14.3
scale(logitpred, scale = F) -0.0044124  0.0014560    -3.0

Correlation of Fixed Effects:
            (Intr) s(_s=F scl(ln,s=F) scl(b,s=F)
scl(l_,s=F) -0.001                              
scl(ln,s=F) -0.001  0.566                       
scl(bg,s=F)  0.002 -0.297 -0.075                
scl(lg,s=F)  0.001 -0.303  0.064      -0.244    
Linear mixed model fit by maximum likelihood 
Formula: log(RPD) ~ scale(log_freq, scale = F) + scale(len, scale = F) +      scale(bigram, scale = F) + scale(logitpred, scale = F) +      scale(surprisalDep, scale = F) + (1 | sn) + (1 | id) 
   Data: d.rpd 
    AIC    BIC logLik deviance REMLdev
 157288 157377 -78635   157270  157337
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0311765 0.17657 
 sn       (Intercept) 0.0052475 0.07244 
 Residual             0.1851956 0.43034 
Number of obs: 135274, groups: id, 222; sn, 144

Fixed effects:
                                 Estimate Std. Error t value
(Intercept)                     5.4721456  0.0133545   409.8
scale(log_freq, scale = F)     -0.0046518  0.0014630    -3.2
scale(len, scale = F)           0.0359462  0.0006313    56.9
scale(bigram, scale = F)       -0.0081844  0.0005319   -15.4
scale(logitpred, scale = F)    -0.0130835  0.0015151    -8.6
scale(surprisalDep, scale = F)  0.0408681  0.0020073    20.4

Correlation of Fixed Effects:
            (Intr) s(_s=F scl(ln,s=F) scl(b,s=F) scl(lg,s=F)
scl(l_,s=F)  0.000                                          
scl(ln,s=F) -0.001  0.564                                   
scl(bg,s=F)  0.001 -0.301 -0.076                            
scl(lg,s=F)  0.000 -0.319  0.056      -0.219                
scl(sD,s=F)  0.004  0.108  0.017      -0.053     -0.281     
Linear mixed model fit by maximum likelihood 
Formula: log(RPD) ~ scale(log_freq, scale = F) + scale(len, scale = F) +      scale(bigram, scale = F) + scale(logitpred, scale = F) +      scale(time, scale = F) + (1 | sn) + (1 | id) 
   Data: d.rpd 
    AIC    BIC logLik deviance REMLdev
 157654 157743 -78818   157636  157713
Random effects:
 Groups   Name        Variance Std.Dev.
 id       (Intercept) 0.031160 0.176522
 sn       (Intercept) 0.004986 0.070611
 Residual             0.185709 0.430939
Number of obs: 135274, groups: id, 222; sn, 144

Fixed effects:
                              Estimate Std. Error t value
(Intercept)                  5.471e+00  1.328e-02   411.8
scale(log_freq, scale = F)  -1.024e-02  1.495e-03    -6.8
scale(len, scale = F)        3.524e-02  6.358e-04    55.4
scale(bigram, scale = F)    -7.832e-03  5.327e-04   -14.7
scale(logitpred, scale = F) -3.590e-03  1.461e-03    -2.5
scale(time, scale = F)      -9.560e-05  1.384e-05    -6.9

Correlation of Fixed Effects:
            (Intr) s(_s=F scl(ln,s=F) scl(b,s=F) scl(lg,s=F)
scl(l_,s=F) -0.001                                          
scl(ln,s=F) -0.001  0.573                                   
scl(bg,s=F)  0.002 -0.276 -0.068                            
scl(lg,s=F)  0.001 -0.312  0.054      -0.248                
scl(tm,s=F)  0.000  0.227  0.111       0.059     -0.082     
Linear mixed model fit by maximum likelihood 
Formula: log(RPD) ~ scale(log_freq, scale = F) + scale(len, scale = F) +      scale(bigram, scale = F) + scale(logitpred, scale = F) +      scale(surprisalDep, scale = F) + scale(time, scale = F) +      (1 | sn) + (1 | id) 
   Data: d.rpd 
    AIC    BIC logLik deviance REMLdev
 157261 157359 -78620   157241  157328
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0311795 0.176577
 sn       (Intercept) 0.0052652 0.072562
 Residual             0.1851540 0.430295
Number of obs: 135274, groups: id, 222; sn, 144

Fixed effects:
                                 Estimate Std. Error t value
(Intercept)                     5.472e+00  1.336e-02   409.6
scale(log_freq, scale = F)     -6.574e-03  1.505e-03    -4.4
scale(len, scale = F)           3.556e-02  6.352e-04    56.0
scale(bigram, scale = F)       -8.344e-03  5.326e-04   -15.7
scale(logitpred, scale = F)    -1.226e-02  1.522e-03    -8.1
scale(surprisalDep, scale = F)  4.007e-02  2.012e-03    19.9
scale(time, scale = F)         -7.567e-05  1.385e-05    -5.5

Correlation of Fixed Effects:
            (Intr) s(_s=F scl(ln,s=F) scl(b,s=F) scl(lg,s=F) s(Ds=F
scl(l_,s=F)  0.000                                                 
scl(ln,s=F) -0.001  0.572                                          
scl(bg,s=F)  0.001 -0.279 -0.070                                   
scl(lg,s=F)  0.000 -0.332  0.044      -0.223                       
scl(sD,s=F)  0.004  0.122  0.025      -0.049     -0.286            
scl(tm,s=F)  0.000  0.234  0.112       0.055     -0.099       0.072
[1] "[TFT]"
Linear mixed model fit by maximum likelihood 
Formula: log(TFT) ~ scale(log_freq, scale = F) + scale(len, scale = F) +      scale(bigram, scale = F) + scale(logitpred, scale = F) +      (1 | sn) + (1 | id) 
   Data: d.tft 
    AIC    BIC logLik deviance REMLdev
 141120 141199 -70552   141104  141161
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0293961 0.171453
 sn       (Intercept) 0.0050166 0.070828
 Residual             0.1643057 0.405346
Number of obs: 135274, groups: id, 222; sn, 144

Fixed effects:
                              Estimate Std. Error t value
(Intercept)                  5.4530181  0.0129827   420.0
scale(log_freq, scale = F)  -0.0009176  0.0013703    -0.7
scale(len, scale = F)        0.0352919  0.0005948    59.3
scale(bigram, scale = F)    -0.0126310  0.0005004   -25.2
scale(logitpred, scale = F) -0.0202836  0.0013699   -14.8

Correlation of Fixed Effects:
            (Intr) s(_s=F scl(ln,s=F) scl(b,s=F)
scl(l_,s=F)  0.000                              
scl(ln,s=F) -0.001  0.566                       
scl(bg,s=F)  0.002 -0.297 -0.076                
scl(lg,s=F)  0.001 -0.303  0.063      -0.245    
Linear mixed model fit by maximum likelihood 
Formula: log(TFT) ~ scale(log_freq, scale = F) + scale(len, scale = F) +      scale(bigram, scale = F) + scale(logitpred, scale = F) +      scale(surprisalDep, scale = F) + (1 | sn) + (1 | id) 
   Data: d.tft 
    AIC    BIC logLik deviance REMLdev
 140786 140874 -70384   140768  140836
Random effects:
 Groups   Name        Variance Std.Dev.
 id       (Intercept) 0.029411 0.171497
 sn       (Intercept) 0.005250 0.072457
 Residual             0.163889 0.404832
Number of obs: 135274, groups: id, 222; sn, 144

Fixed effects:
                                 Estimate Std. Error t value
(Intercept)                     5.4540522  0.0130485   418.0
scale(log_freq, scale = F)      0.0018274  0.0013769     1.3
scale(len, scale = F)           0.0354774  0.0005942    59.7
scale(bigram, scale = F)       -0.0131107  0.0005006   -26.2
scale(logitpred, scale = F)    -0.0276416  0.0014260   -19.4
scale(surprisalDep, scale = F)  0.0346538  0.0018891    18.3

Correlation of Fixed Effects:
            (Intr) s(_s=F scl(ln,s=F) scl(b,s=F) scl(lg,s=F)
scl(l_,s=F)  0.000                                          
scl(ln,s=F) -0.001  0.565                                   
scl(bg,s=F)  0.001 -0.301 -0.077                            
scl(lg,s=F)  0.000 -0.320  0.056      -0.220                
scl(sD,s=F)  0.004  0.108  0.017      -0.053     -0.281     
Linear mixed model fit by maximum likelihood 
Formula: log(TFT) ~ scale(log_freq, scale = F) + scale(len, scale = F) +      scale(bigram, scale = F) + scale(logitpred, scale = F) +      scale(time, scale = F) + (1 | sn) + (1 | id) 
   Data: d.tft 
    AIC    BIC logLik deviance REMLdev
 141077 141166 -70530   141059  141137
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0293990 0.171461
 sn       (Intercept) 0.0050221 0.070867
 Residual             0.1642511 0.405279
Number of obs: 135274, groups: id, 222; sn, 144

Fixed effects:
                              Estimate Std. Error t value
(Intercept)                  5.453e+00  1.299e-02   419.9
scale(log_freq, scale = F)  -3.056e-03  1.407e-03    -2.2
scale(len, scale = F)        3.485e-02  5.983e-04    58.2
scale(bigram, scale = F)    -1.283e-02  5.012e-04   -25.6
scale(logitpred, scale = F) -1.953e-02  1.374e-03   -14.2
scale(time, scale = F)      -8.697e-05  1.302e-05    -6.7

Correlation of Fixed Effects:
            (Intr) s(_s=F scl(ln,s=F) scl(b,s=F) scl(lg,s=F)
scl(l_,s=F) -0.001                                          
scl(ln,s=F) -0.001  0.573                                   
scl(bg,s=F)  0.002 -0.275 -0.069                            
scl(lg,s=F)  0.001 -0.313  0.054      -0.248                
scl(tm,s=F)  0.000  0.228  0.111       0.059     -0.082     
Linear mixed model fit by maximum likelihood 
Formula: log(TFT) ~ scale(log_freq, scale = F) + scale(len, scale = F) +      scale(bigram, scale = F) + scale(logitpred, scale = F) +      scale(surprisalDep, scale = F) + scale(time, scale = F) +      (1 | sn) + (1 | id) 
   Data: d.tft 
    AIC    BIC logLik deviance REMLdev
 140759 140857 -70370   140739  140827
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0294136 0.171504
 sn       (Intercept) 0.0052615 0.072536
 Residual             0.1638537 0.404789
Number of obs: 135274, groups: id, 222; sn, 144

Fixed effects:
                                 Estimate Std. Error t value
(Intercept)                     5.454e+00  1.305e-02   417.9
scale(log_freq, scale = F)      4.435e-05  1.416e-03  0.0313
scale(len, scale = F)           3.512e-02  5.980e-04    58.7
scale(bigram, scale = F)       -1.326e-02  5.013e-04   -26.4
scale(logitpred, scale = F)    -2.688e-02  1.433e-03   -18.8
scale(surprisalDep, scale = F)  3.392e-02  1.894e-03    17.9
scale(time, scale = F)         -7.015e-05  1.304e-05    -5.4

Correlation of Fixed Effects:
            (Intr) s(_s=F scl(ln,s=F) scl(b,s=F) scl(lg,s=F) s(Ds=F
scl(l_,s=F)  0.000                                                 
scl(ln,s=F) -0.001  0.572                                          
scl(bg,s=F)  0.001 -0.279 -0.070                                   
scl(lg,s=F)  0.000 -0.332  0.044      -0.224                       
scl(sD,s=F)  0.004  0.122  0.025      -0.049     -0.286            
scl(tm,s=F)  0.000  0.234  0.112       0.055     -0.099       0.072
[1] "[REG]"
Generalized linear mixed model fit by the Laplace approximation 
Formula: reg ~ scale(log_freq, scale = F) + scale(len, scale = F) + scale(bigram,      scale = F) + scale(logitpred, scale = F) + (1 | sn) + (1 |      id) 
   Data: d.reg 
   AIC   BIC logLik deviance
 86505 86574 -43246    86491
Random effects:
 Groups Name        Variance Std.Dev.
 id     (Intercept) 0.70427  0.83921 
 sn     (Intercept) 0.09918  0.31493 
Number of obs: 135274, groups: id, 222; sn, 144

Fixed effects:
                             Estimate Std. Error z value Pr(>|z|)    
(Intercept)                 -2.364237   0.063185  -37.42  < 2e-16 ***
scale(log_freq, scale = F)  -0.172153   0.011039  -15.60  < 2e-16 ***
scale(len, scale = F)        0.013886   0.004571    3.04  0.00239 ** 
scale(bigram, scale = F)     0.083167   0.004105   20.26  < 2e-16 ***
scale(logitpred, scale = F)  0.051925   0.011063    4.69 2.69e-06 ***
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 

Correlation of Fixed Effects:
            (Intr) s(_s=F scl(ln,s=F) scl(b,s=F)
scl(l_,s=F)  0.015                              
scl(ln,s=F) -0.004  0.539                       
scl(bg,s=F) -0.018 -0.337 -0.071                
scl(lg,s=F) -0.003 -0.283  0.069      -0.263    
Generalized linear mixed model fit by the Laplace approximation 
Formula: reg ~ scale(log_freq, scale = F) + scale(len, scale = F) + scale(bigram,      scale = F) + scale(logitpred, scale = F) + scale(surprisalDep,      scale = F) + (1 | sn) + (1 | id) 
   Data: d.reg 
   AIC   BIC logLik deviance
 86392 86470 -43188    86376
Random effects:
 Groups Name        Variance Std.Dev.
 id     (Intercept) 0.70572  0.84007 
 sn     (Intercept) 0.10155  0.31867 
Number of obs: 135274, groups: id, 222; sn, 144

Fixed effects:
                                Estimate Std. Error z value Pr(>|z|)    
(Intercept)                    -2.363182   0.063369  -37.29  < 2e-16 ***
scale(log_freq, scale = F)     -0.158560   0.011076  -14.32  < 2e-16 ***
scale(len, scale = F)           0.014024   0.004575    3.07  0.00217 ** 
scale(bigram, scale = F)        0.080269   0.004106   19.55  < 2e-16 ***
scale(logitpred, scale = F)     0.016538   0.011539    1.43  0.15179    
scale(surprisalDep, scale = F)  0.162905   0.015103   10.79  < 2e-16 ***
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 

Correlation of Fixed Effects:
            (Intr) s(_s=F scl(ln,s=F) scl(b,s=F) scl(lg,s=F)
scl(l_,s=F)  0.015                                          
scl(ln,s=F) -0.003  0.538                                   
scl(bg,s=F) -0.017 -0.341 -0.071                            
scl(lg,s=F) -0.001 -0.299  0.065      -0.231                
scl(sD,s=F) -0.003  0.112  0.002      -0.068     -0.284     
Generalized linear mixed model fit by the Laplace approximation 
Formula: reg ~ scale(log_freq, scale = F) + scale(len, scale = F) + scale(bigram,      scale = F) + scale(logitpred, scale = F) + scale(time, scale = F) +      (1 | sn) + (1 | id) 
   Data: d.reg 
   AIC   BIC logLik deviance
 87842 87920 -43913    87826
Random effects:
 Groups Name        Variance Std.Dev.
 id     (Intercept) 0.057856 0.24053 
 sn     (Intercept) 0.014517 0.12049 
Number of obs: 135274, groups: id, 222; sn, 144

Fixed effects:
                              Estimate Std. Error z value Pr(>|z|)    
(Intercept)                 -2.1049325  0.0213380  -98.65  < 2e-16 ***
scale(log_freq, scale = F)  -0.1688298  0.0107757  -15.67  < 2e-16 ***
scale(len, scale = F)        0.0035928  0.0043425    0.83 0.408042    
scale(bigram, scale = F)     0.0720178  0.0038732   18.59  < 2e-16 ***
scale(logitpred, scale = F)  0.0368177  0.0105536    3.49 0.000486 ***
scale(time, scale = F)      -0.0003104  0.0001003   -3.10 0.001959 ** 
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 

Correlation of Fixed Effects:
            (Intr) s(_s=F scl(ln,s=F) scl(b,s=F) scl(lg,s=F)
scl(l_,s=F)  0.043                                          
scl(ln,s=F) -0.002  0.533                                   
scl(bg,s=F) -0.046 -0.335 -0.051                            
scl(lg,s=F) -0.005 -0.284  0.072      -0.249                
scl(tm,s=F)  0.007  0.224  0.115       0.043     -0.086     
Generalized linear mixed model fit by the Laplace approximation 
Formula: reg ~ scale(log_freq, scale = F) + scale(len, scale = F) + scale(bigram,      scale = F) + scale(logitpred, scale = F) + scale(surprisalDep,      scale = F) + scale(time, scale = F) + (1 | sn) + (1 | id) 
   Data: d.reg 
   AIC   BIC logLik deviance
 87383 87471 -43682    87365
Random effects:
 Groups Name        Variance Std.Dev.
 id     (Intercept) 0.079026 0.28112 
 sn     (Intercept) 0.018809 0.13714 
Number of obs: 135274, groups: id, 222; sn, 144

Fixed effects:
                                 Estimate Std. Error z value Pr(>|z|)    
(Intercept)                    -2.1136668  0.0241822  -87.41  < 2e-16 ***
scale(log_freq, scale = F)     -0.1583280  0.0109390  -14.47  < 2e-16 ***
scale(len, scale = F)           0.0058156  0.0043890    1.33  0.18516    
scale(bigram, scale = F)        0.0703978  0.0039147   17.98  < 2e-16 ***
scale(logitpred, scale = F)     0.0149387  0.0110622    1.35  0.17688    
scale(surprisalDep, scale = F)  0.1281461  0.0143923    8.90  < 2e-16 ***
scale(time, scale = F)         -0.0002685  0.0001017   -2.64  0.00828 ** 
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 

Correlation of Fixed Effects:
            (Intr) s(_s=F scl(ln,s=F) scl(b,s=F) scl(lg,s=F) s(Ds=F
scl(l_,s=F)  0.037                                                 
scl(ln,s=F) -0.003  0.536                                          
scl(bg,s=F) -0.040 -0.338 -0.055                                   
scl(lg,s=F) -0.003 -0.305  0.060      -0.217                       
scl(sD,s=F) -0.008  0.125  0.022      -0.081     -0.275            
scl(tm,s=F)  0.006  0.235  0.117       0.032     -0.099       0.080
