[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
 42834 42920 -21408    42816   42886
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0150452 0.122659
 sn       (Intercept) 0.0014145 0.037610
 Residual             0.0883528 0.297242
Number of obs: 100860, groups: id, 222; sn, 144

Fixed effects:
                                 Estimate Std. Error t value
(Intercept)                     5.2759320  0.0088646   595.2
scale(log_freq, scale = F)     -0.0003093  0.0011613    -0.3
scale(len, scale = F)           0.0059453  0.0005687    10.5
scale(bigram, scale = F)       -0.0129602  0.0004114   -31.5
scale(logitpred, scale = F)    -0.0123905  0.0011674   -10.6
scale(surprisalDep, scale = F)  0.0305096  0.0015393    19.8

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  0.564                                   
scl(bg,s=F)  0.004 -0.289 -0.068                            
scl(lg,s=F)  0.000 -0.302  0.070      -0.223                
scl(sD,s=F)  0.006  0.094  0.018      -0.036     -0.260     
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
 43214 43300 -21598    43196   43276
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0150389 0.122633
 sn       (Intercept) 0.0012771 0.035737
 Residual             0.0886989 0.297824
Number of obs: 100860, groups: id, 222; sn, 144

Fixed effects:
                              Estimate Std. Error t value
(Intercept)                  5.275e+00  8.809e-03   598.8
scale(log_freq, scale = F)  -1.440e-03  1.196e-03    -1.2
scale(len, scale = F)        5.893e-03  5.704e-04    10.3
scale(bigram, scale = F)    -1.261e-02  4.120e-04   -30.6
scale(logitpred, scale = F) -6.719e-03  1.133e-03    -5.9
scale(time, scale = F)       3.971e-05  1.155e-05     3.4

Correlation of Fixed Effects:
            (Intr) s(_s=F scl(ln,s=F) scl(b,s=F) scl(lg,s=F)
scl(l_,s=F) -0.002                                          
scl(ln,s=F) -0.002  0.563                                   
scl(bg,s=F)  0.004 -0.266 -0.063                            
scl(lg,s=F)  0.001 -0.301  0.071      -0.243                
scl(tm,s=F)  0.000  0.254  0.071       0.046     -0.092     
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
 42813 42908 -21397    42793   42884
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0150364 0.122623
 sn       (Intercept) 0.0014177 0.037653
 Residual             0.0883321 0.297207
Number of obs: 100860, groups: id, 222; sn, 144

Fixed effects:
                                 Estimate Std. Error t value
(Intercept)                     5.276e+00  8.864e-03   595.2
scale(log_freq, scale = F)      1.198e-03  1.202e-03     1.0
scale(len, scale = F)           6.144e-03  5.701e-04    10.8
scale(bigram, scale = F)       -1.287e-02  4.118e-04   -31.3
scale(logitpred, scale = F)    -1.300e-02  1.174e-03   -11.1
scale(surprisalDep, scale = F)  3.103e-02  1.543e-03    20.1
scale(time, scale = F)          5.594e-05  1.156e-05     4.8

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  0.562                                          
scl(bg,s=F)  0.004 -0.267 -0.064                                   
scl(lg,s=F)  0.000 -0.317  0.062      -0.226                       
scl(sD,s=F)  0.006  0.109  0.023      -0.033     -0.266            
scl(tm,s=F)  0.001  0.259  0.072       0.044     -0.107       0.069
[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
 51746 51834 -25864    51728   51799
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0143780 0.119908
 sn       (Intercept) 0.0012109 0.034798
 Residual             0.0872616 0.295401
Number of obs: 126198, groups: id, 222; sn, 144

Fixed effects:
                                 Estimate Std. Error t value
(Intercept)                     5.2728850  0.0085983   613.2
scale(log_freq, scale = F)      0.0048599  0.0010460     4.6
scale(len, scale = F)          -0.0020387  0.0004429    -4.6
scale(bigram, scale = F)       -0.0136338  0.0003809   -35.8
scale(logitpred, scale = F)    -0.0100815  0.0010766    -9.4
scale(surprisalDep, scale = F)  0.0390634  0.0013751    28.4

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  0.547                                   
scl(bg,s=F)  0.001 -0.311 -0.072                            
scl(lg,s=F)  0.000 -0.311  0.059      -0.225                
scl(sD,s=F)  0.004  0.104  0.010      -0.042     -0.278     
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
 52541 52629 -26262    52523   52604
Random effects:
 Groups   Name        Variance   Std.Dev.
 id       (Intercept) 0.01436879 0.119870
 sn       (Intercept) 0.00099706 0.031576
 Residual             0.08783249 0.296365
Number of obs: 126198, groups: id, 222; sn, 144

Fixed effects:
                              Estimate Std. Error t value
(Intercept)                  5.272e+00  8.508e-03   619.6
scale(log_freq, scale = F)   2.459e-03  1.074e-03     2.3
scale(len, scale = F)       -2.018e-03  4.451e-04    -4.5
scale(bigram, scale = F)    -1.316e-02  3.816e-04   -34.5
scale(logitpred, scale = F) -1.834e-03  1.041e-03    -1.8
scale(time, scale = F)       2.683e-05  1.015e-05     2.6

Correlation of Fixed Effects:
            (Intr) s(_s=F scl(ln,s=F) scl(b,s=F) scl(lg,s=F)
scl(l_,s=F)  0.000                                          
scl(ln,s=F) -0.001  0.552                                   
scl(bg,s=F)  0.001 -0.288 -0.066                            
scl(lg,s=F)  0.001 -0.308  0.056      -0.249                
scl(tm,s=F)  0.000  0.242  0.093       0.049     -0.096     
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
 51727 51825 -25854    51707   51800
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0143745 0.119894
 sn       (Intercept) 0.0012134 0.034834
 Residual             0.0872471 0.295376
Number of obs: 126198, groups: id, 222; sn, 144

Fixed effects:
                                 Estimate Std. Error t value
(Intercept)                     5.273e+00  8.598e-03   613.2
scale(log_freq, scale = F)      6.080e-03  1.080e-03     5.6
scale(len, scale = F)          -1.848e-03  4.448e-04    -4.2
scale(bigram, scale = F)       -1.355e-02  3.813e-04   -35.5
scale(logitpred, scale = F)    -1.063e-02  1.083e-03    -9.8
scale(surprisalDep, scale = F)  3.948e-02  1.378e-03    28.6
scale(time, scale = F)          4.631e-05  1.016e-05     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  0.551                                          
scl(bg,s=F)  0.001 -0.289 -0.067                                   
scl(lg,s=F)  0.000 -0.327  0.048      -0.228                       
scl(sD,s=F)  0.004  0.117  0.016      -0.039     -0.283            
scl(tm,s=F)  0.000  0.248  0.094       0.047     -0.111       0.066
[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
 157366 157454 -78674   157348  157414
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0311747 0.176564
 sn       (Intercept) 0.0052265 0.072295
 Residual             0.1853022 0.430467
Number of obs: 135274, groups: id, 222; sn, 144

Fixed effects:
                                 Estimate Std. Error t value
(Intercept)                     5.4719938  0.0133488   409.9
scale(log_freq, scale = F)     -0.0051878  0.0014622    -3.5
scale(len, scale = F)           0.0358671  0.0006314    56.8
scale(bigram, scale = F)       -0.0079489  0.0005316   -15.0
scale(logitpred, scale = F)    -0.0121587  0.0015144    -8.0
scale(surprisalDep, scale = F)  0.0356572  0.0019417    18.4

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)  0.002 -0.299 -0.076                            
scl(lg,s=F)  0.000 -0.317  0.058      -0.225                
scl(sD,s=F)  0.004  0.100  0.012      -0.035     -0.279     
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
 157666 157754 -78824   157648  157724
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0311591 0.176519
 sn       (Intercept) 0.0049588 0.070419
 Residual             0.1857250 0.430958
Number of obs: 135274, groups: id, 222; sn, 144

Fixed effects:
                              Estimate Std. Error t value
(Intercept)                  5.471e+00  1.328e-02   412.1
scale(log_freq, scale = F)  -1.014e-02  1.503e-03    -6.7
scale(len, scale = F)        3.538e-02  6.344e-04    55.8
scale(bigram, scale = F)    -7.767e-03  5.324e-04   -14.6
scale(logitpred, scale = F) -3.592e-03  1.462e-03    -2.5
scale(time, scale = F)      -8.680e-05  1.436e-05    -6.0

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  0.568                                   
scl(bg,s=F)  0.002 -0.276 -0.071                            
scl(lg,s=F)  0.001 -0.315  0.055      -0.247                
scl(tm,s=F)  0.000  0.247  0.089       0.046     -0.093     
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
 157343 157441 -78662   157323  157411
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0311770 0.176570
 sn       (Intercept) 0.0052181 0.072237
 Residual             0.1852691 0.430429
Number of obs: 135274, groups: id, 222; sn, 144

Fixed effects:
                                 Estimate Std. Error t value
(Intercept)                     5.472e+00  1.335e-02   409.9
scale(log_freq, scale = F)     -7.068e-03  1.511e-03    -4.7
scale(len, scale = F)           3.559e-02  6.339e-04    56.1
scale(bigram, scale = F)       -8.066e-03  5.321e-04   -15.2
scale(logitpred, scale = F)    -1.136e-02  1.523e-03    -7.5
scale(surprisalDep, scale = F)  3.507e-02  1.945e-03    18.0
scale(time, scale = F)         -7.090e-05  1.437e-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)  0.000                                                 
scl(ln,s=F) -0.001  0.567                                          
scl(bg,s=F)  0.002 -0.278 -0.072                                   
scl(lg,s=F)  0.000 -0.332  0.048      -0.228                       
scl(sD,s=F)  0.004  0.112  0.018      -0.032     -0.283            
scl(tm,s=F)  0.000  0.252  0.090       0.044     -0.106       0.061
[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
 140851 140939 -70417   140833  140901
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0294102 0.171494
 sn       (Intercept) 0.0052304 0.072322
 Residual             0.1639689 0.404931
Number of obs: 135274, groups: id, 222; sn, 144

Fixed effects:
                                 Estimate Std. Error t value
(Intercept)                     5.4539188  0.0130422   418.2
scale(log_freq, scale = F)      0.0013624  0.0013760     1.0
scale(len, scale = F)           0.0354101  0.0005943    59.6
scale(bigram, scale = F)       -0.0129100  0.0005003   -25.8
scale(logitpred, scale = F)    -0.0268270  0.0014252   -18.8
scale(surprisalDep, scale = F)  0.0300977  0.0018272    16.5

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)  0.002 -0.299 -0.076                            
scl(lg,s=F)  0.000 -0.317  0.058      -0.225                
scl(sD,s=F)  0.004  0.100  0.012      -0.035     -0.279     
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
 141097 141185 -70539   141079  141156
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0293980 0.171459
 sn       (Intercept) 0.0049987 0.070701
 Residual             0.1642756 0.405309
Number of obs: 135274, groups: id, 222; sn, 144

Fixed effects:
                              Estimate Std. Error t value
(Intercept)                  5.453e+00  1.298e-02   420.1
scale(log_freq, scale = F)  -2.677e-03  1.414e-03    -1.9
scale(len, scale = F)        3.502e-02  5.971e-04    58.7
scale(bigram, scale = F)    -1.275e-02  5.009e-04   -25.5
scale(logitpred, scale = F) -1.964e-02  1.376e-03   -14.3
scale(time, scale = F)      -6.788e-05  1.351e-05    -5.0

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  0.568                                   
scl(bg,s=F)  0.002 -0.276 -0.071                            
scl(lg,s=F)  0.001 -0.315  0.055      -0.248                
scl(tm,s=F)  0.000  0.248  0.089       0.047     -0.093     
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
 140837 140935 -70408   140817  140905
Random effects:
 Groups   Name        Variance Std.Dev.
 id       (Intercept) 0.029411 0.171497
 sn       (Intercept) 0.005219 0.072242
 Residual             0.163950 0.404907
Number of obs: 135274, groups: id, 222; sn, 144

Fixed effects:
                                 Estimate Std. Error t value
(Intercept)                     5.454e+00  1.304e-02   418.3
scale(log_freq, scale = F)     -8.330e-05  1.422e-03    -0.1
scale(len, scale = F)           3.519e-02  5.967e-04    59.0
scale(bigram, scale = F)       -1.300e-02  5.008e-04   -26.0
scale(logitpred, scale = F)    -2.621e-02  1.433e-03   -18.3
scale(surprisalDep, scale = F)  2.965e-02  1.831e-03    16.2
scale(time, scale = F)         -5.447e-05  1.353e-05    -4.0

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  0.567                                          
scl(bg,s=F)  0.002 -0.278 -0.072                                   
scl(lg,s=F)  0.000 -0.332  0.047      -0.228                       
scl(sD,s=F)  0.004  0.112  0.017      -0.032     -0.283            
scl(tm,s=F)  0.000  0.252  0.090       0.045     -0.106       0.061
[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
 86419 86497 -43201    86403
Random effects:
 Groups Name        Variance Std.Dev.
 id     (Intercept) 0.70542  0.83989 
 sn     (Intercept) 0.10097  0.31775 
Number of obs: 135274, groups: id, 222; sn, 144

Fixed effects:
                                Estimate Std. Error z value Pr(>|z|)    
(Intercept)                    -2.363050   0.063326  -37.32  < 2e-16 ***
scale(log_freq, scale = F)     -0.161102   0.011069  -14.55  < 2e-16 ***
scale(len, scale = F)           0.013731   0.004573    3.00  0.00268 ** 
scale(bigram, scale = F)        0.081320   0.004102   19.82  < 2e-16 ***
scale(logitpred, scale = F)     0.021091   0.011536    1.83  0.06750 .  
scale(surprisalDep, scale = F)  0.138517   0.014660    9.45  < 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  0.537                                   
scl(bg,s=F) -0.018 -0.339 -0.071                            
scl(lg,s=F) -0.002 -0.298  0.067      -0.237                
scl(sD,s=F) -0.002  0.104 -0.005      -0.049     -0.282     
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
 86997 87075 -43490    86981
Random effects:
 Groups Name        Variance Std.Dev.
 id     (Intercept) 0.140759 0.37518 
 sn     (Intercept) 0.026976 0.16424 
Number of obs: 135274, groups: id, 222; sn, 144

Fixed effects:
                              Estimate Std. Error z value Pr(>|z|)    
(Intercept)                 -2.2207027  0.0304786  -72.86  < 2e-16 ***
scale(log_freq, scale = F)  -0.1760834  0.0111165  -15.84  < 2e-16 ***
scale(len, scale = F)        0.0039582  0.0044779    0.88  0.37672    
scale(bigram, scale = F)     0.0926807  0.0039658   23.37  < 2e-16 ***
scale(logitpred, scale = F)  0.0466354  0.0107808    4.33 1.52e-05 ***
scale(time, scale = F)      -0.0003244  0.0001068   -3.04  0.00239 ** 
---
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)  0.032                                          
scl(ln,s=F) -0.002  0.536                                   
scl(bg,s=F) -0.042 -0.334 -0.058                            
scl(lg,s=F) -0.005 -0.287  0.068      -0.255                
scl(tm,s=F)  0.006  0.242  0.091       0.028     -0.091     
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
 87543 87631 -43763    87525
Random effects:
 Groups Name        Variance Std.Dev.
 id     (Intercept) 0.067802 0.26039 
 sn     (Intercept) 0.018491 0.13598 
Number of obs: 135274, groups: id, 222; sn, 144

Fixed effects:
                                 Estimate Std. Error z value Pr(>|z|)    
(Intercept)                    -2.1155503  0.0230281  -91.87  < 2e-16 ***
scale(log_freq, scale = F)     -0.1632588  0.0109491  -14.91  < 2e-16 ***
scale(len, scale = F)           0.0054336  0.0043693    1.24 0.213647    
scale(bigram, scale = F)        0.0714419  0.0039037   18.30  < 2e-16 ***
scale(logitpred, scale = F)     0.0195763  0.0110445    1.77 0.076311 .  
scale(surprisalDep, scale = F)  0.1090409  0.0139405    7.82  5.2e-15 ***
scale(time, scale = F)         -0.0003497  0.0001053   -3.32 0.000901 ***
---
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)  0.040                                                 
scl(ln,s=F) -0.003  0.530                                          
scl(bg,s=F) -0.043 -0.339 -0.056                                   
scl(lg,s=F) -0.004 -0.304  0.064      -0.222                       
scl(sD,s=F) -0.006  0.113  0.012      -0.064     -0.272            
scl(tm,s=F)  0.009  0.246  0.092       0.019     -0.100       0.060
