[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
 42753 42839 -21367    42735   42805
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0150483 0.122671
 sn       (Intercept) 0.0014374 0.037914
 Residual             0.0882793 0.297118
Number of obs: 100860, groups: id, 222; sn, 144

Fixed effects:
                                 Estimate Std. Error t value
(Intercept)                     5.2761246  0.0088743   594.5
scale(log_freq, scale = F)      0.0005917  0.0011644     0.5
scale(len, scale = F)           0.0060219  0.0005686    10.6
scale(bigram, scale = F)       -0.0133217  0.0004121   -32.3
scale(logitpred, scale = F)    -0.0132545  0.0011703   -11.3
scale(surprisalDep, scale = F)  0.0361958  0.0016607    21.8

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 -0.293 -0.069                            
scl(lg,s=F) -0.001 -0.308  0.068      -0.211                
scl(sD,s=F)  0.006  0.121  0.023      -0.074     -0.270     
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
 43192 43278 -21587    43174   43254
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0150327 0.122608
 sn       (Intercept) 0.0012698 0.035634
 Residual             0.0886807 0.297793
Number of obs: 100860, groups: id, 222; sn, 144

Fixed effects:
                              Estimate Std. Error t value
(Intercept)                  5.275e+00  8.805e-03   599.1
scale(log_freq, scale = F)  -1.408e-03  1.172e-03    -1.2
scale(len, scale = F)        6.108e-03  5.721e-04    10.7
scale(bigram, scale = F)    -1.240e-02  4.142e-04   -29.9
scale(logitpred, scale = F) -6.809e-03  1.131e-03    -6.0
scale(time, scale = F)       6.030e-05  1.043e-05     5.8

Correlation of Fixed Effects:
            (Intr) s(_s=F scl(ln,s=F) scl(b,s=F) scl(lg,s=F)
scl(l_,s=F) -0.002                                          
scl(ln,s=F) -0.002  0.571                                   
scl(bg,s=F)  0.004 -0.264 -0.054                            
scl(lg,s=F)  0.001 -0.295  0.070      -0.246                
scl(tm,s=F) -0.001  0.159  0.107       0.114     -0.069     
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
 42671 42767 -21326    42651   42742
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0150284 0.12259 
 sn       (Intercept) 0.0014251 0.03775 
 Residual             0.0882072 0.29700 
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)      2.502e-03  1.182e-03     2.1
scale(len, scale = F)           6.605e-03  5.719e-04    11.5
scale(bigram, scale = F)       -1.293e-02  4.142e-04   -31.2
scale(logitpred, scale = F)    -1.440e-02  1.177e-03   -12.2
scale(surprisalDep, scale = F)  3.847e-02  1.679e-03    22.9
scale(time, scale = F)          9.625e-05  1.053e-05     9.1

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) -0.001                                                 
scl(ln,s=F) -0.002  0.571                                          
scl(bg,s=F)  0.004 -0.268 -0.056                                   
scl(lg,s=F) -0.001 -0.321  0.056      -0.220                       
scl(sD,s=F)  0.006  0.144  0.039      -0.057     -0.281            
scl(tm,s=F) -0.001  0.177  0.111       0.104     -0.107       0.149
[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
 51643 51730 -25812    51625   51696
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0143803 0.119918
 sn       (Intercept) 0.0012321 0.035101
 Residual             0.0871882 0.295276
Number of obs: 126198, groups: id, 222; sn, 144

Fixed effects:
                                 Estimate Std. Error t value
(Intercept)                     5.2730649  0.0086075   612.6
scale(log_freq, scale = F)      0.0059087  0.0010490     5.6
scale(len, scale = F)          -0.0019728  0.0004428    -4.5
scale(bigram, scale = F)       -0.0140986  0.0003817   -36.9
scale(logitpred, scale = F)    -0.0108744  0.0010787   -10.1
scale(surprisalDep, scale = F)  0.0448226  0.0014844    30.2

Correlation of Fixed Effects:
            (Intr) s(_s=F scl(ln,s=F) scl(b,s=F) scl(lg,s=F)
scl(l_,s=F)  0.001                                          
scl(ln,s=F) -0.001  0.547                                   
scl(bg,s=F)  0.001 -0.315 -0.073                            
scl(lg,s=F)  0.000 -0.318  0.058      -0.213                
scl(sD,s=F)  0.005  0.131  0.015      -0.080     -0.286     
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
 52521 52608 -26251    52503   52584
Random effects:
 Groups   Name        Variance Std.Dev.
 id       (Intercept) 0.014366 0.119858
 sn       (Intercept) 0.000989 0.031449
 Residual             0.087819 0.296342
Number of obs: 126198, groups: id, 222; sn, 144

Fixed effects:
                              Estimate Std. Error t value
(Intercept)                  5.272e+00  8.505e-03   619.8
scale(log_freq, scale = F)   2.557e-03  1.052e-03     2.4
scale(len, scale = F)       -1.822e-03  4.468e-04    -4.1
scale(bigram, scale = F)    -1.296e-02  3.838e-04   -33.8
scale(logitpred, scale = F) -1.968e-03  1.038e-03    -1.9
scale(time, scale = F)       4.874e-05  9.257e-06     5.3

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 -0.054                            
scl(lg,s=F)  0.001 -0.301  0.055      -0.252                
scl(tm,s=F) -0.001  0.142  0.129       0.119     -0.073     
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
 51554 51651 -25767    51534   51626
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0143732 0.119888
 sn       (Intercept) 0.0012147 0.034853
 Residual             0.0871266 0.295172
Number of obs: 126198, groups: id, 222; sn, 144

Fixed effects:
                                 Estimate Std. Error t value
(Intercept)                     5.273e+00  8.598e-03   613.3
scale(log_freq, scale = F)      7.523e-03  1.062e-03     7.1
scale(len, scale = F)          -1.406e-03  4.465e-04    -3.1
scale(bigram, scale = F)       -1.370e-02  3.838e-04   -35.7
scale(logitpred, scale = F)    -1.201e-02  1.085e-03   -11.1
scale(surprisalDep, scale = F)  4.678e-02  1.498e-03    31.2
scale(time, scale = F)          8.891e-05  9.323e-06     9.5

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  0.556                                          
scl(bg,s=F)  0.001 -0.292 -0.057                                   
scl(lg,s=F)  0.000 -0.329  0.042      -0.222                       
scl(sD,s=F)  0.005  0.150  0.033      -0.064     -0.296            
scl(tm,s=F) -0.001  0.160  0.133       0.110     -0.110       0.138
[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
 157229 157317 -78605   157211  157278
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0311811 0.176582
 sn       (Intercept) 0.0052641 0.072554
 Residual             0.1851132 0.430248
Number of obs: 135274, groups: id, 222; sn, 144

Fixed effects:
                                 Estimate Std. Error t value
(Intercept)                     5.4723062  0.0133598   409.6
scale(log_freq, scale = F)     -0.0038390  0.0014659    -2.6
scale(len, scale = F)           0.0359590  0.0006311    57.0
scale(bigram, scale = F)       -0.0084284  0.0005324   -15.8
scale(logitpred, scale = F)    -0.0138637  0.0015171    -9.1
scale(surprisalDep, scale = F)  0.0456550  0.0020962    21.8

Correlation of Fixed Effects:
            (Intr) s(_s=F scl(ln,s=F) scl(b,s=F) scl(lg,s=F)
scl(l_,s=F)  0.000                                          
scl(ln,s=F) -0.001  0.563                                   
scl(bg,s=F)  0.001 -0.303 -0.077                            
scl(lg,s=F) -0.001 -0.324  0.056      -0.213                
scl(sD,s=F)  0.005  0.126  0.017      -0.071     -0.286     
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
 157697 157786 -78840   157679  157756
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0311557 0.176510
 sn       (Intercept) 0.0049823 0.070586
 Residual             0.1857678 0.431008
Number of obs: 135274, groups: id, 222; sn, 144

Fixed effects:
                              Estimate Std. Error t value
(Intercept)                  5.471e+00  1.328e-02   411.9
scale(log_freq, scale = F)  -8.365e-03  1.472e-03    -5.7
scale(len, scale = F)        3.555e-02  6.369e-04    55.8
scale(bigram, scale = F)    -7.750e-03  5.353e-04   -14.5
scale(logitpred, scale = F) -4.197e-03  1.459e-03    -2.9
scale(time, scale = F)      -2.847e-05  1.302e-05    -2.2

Correlation of Fixed Effects:
            (Intr) s(_s=F scl(ln,s=F) scl(b,s=F) scl(lg,s=F)
scl(l_,s=F) -0.001                                          
scl(ln,s=F) -0.001  0.574                                   
scl(bg,s=F)  0.002 -0.275 -0.060                            
scl(lg,s=F)  0.001 -0.309  0.055      -0.250                
scl(tm,s=F) -0.001  0.147  0.125       0.114     -0.067     
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
 157230 157328 -78605   157210  157298
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0311806 0.176580
 sn       (Intercept) 0.0052608 0.072531
 Residual             0.1851124 0.430247
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)     -3.643e-03  1.486e-03    -2.5
scale(len, scale = F)           3.602e-02  6.364e-04    56.6
scale(bigram, scale = F)       -8.383e-03  5.353e-04   -15.7
scale(logitpred, scale = F)    -1.399e-02  1.525e-03    -9.2
scale(surprisalDep, scale = F)  4.589e-02  2.116e-03    21.7
scale(time, scale = F)          1.053e-05  1.312e-05     0.8

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)  0.000                                                 
scl(ln,s=F) -0.001  0.572                                          
scl(bg,s=F)  0.001 -0.280 -0.062                                   
scl(lg,s=F)  0.000 -0.335  0.042      -0.222                       
scl(sD,s=F)  0.005  0.146  0.034      -0.055     -0.296            
scl(tm,s=F) -0.001  0.165  0.128       0.105     -0.104       0.137
[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
 140727 140816 -70355   140709  140777
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0294155 0.17151 
 sn       (Intercept) 0.0052708 0.07260 
 Residual             0.1638171 0.40474 
Number of obs: 135274, groups: id, 222; sn, 144

Fixed effects:
                                 Estimate Std. Error t value
(Intercept)                     5.4542048  0.0130538   417.8
scale(log_freq, scale = F)      0.0025632  0.0013796     1.9
scale(len, scale = F)           0.0354906  0.0005941    59.7
scale(bigram, scale = F)       -0.0133267  0.0005010   -26.6
scale(logitpred, scale = F)    -0.0284129  0.0014279   -19.9
scale(surprisalDep, scale = F)  0.0392379  0.0019728    19.9

Correlation of Fixed Effects:
            (Intr) s(_s=F scl(ln,s=F) scl(b,s=F) scl(lg,s=F)
scl(l_,s=F)  0.000                                          
scl(ln,s=F) -0.001  0.564                                   
scl(bg,s=F)  0.001 -0.303 -0.077                            
scl(lg,s=F)  0.000 -0.324  0.056      -0.214                
scl(sD,s=F)  0.005  0.127  0.017      -0.071     -0.286     
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
 141107 141195 -70544   141089  141166
Random effects:
 Groups   Name        Variance Std.Dev.
 id       (Intercept) 0.029395 0.171451
 sn       (Intercept) 0.005029 0.070915
 Residual             0.164287 0.405323
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)  -1.715e-03  1.385e-03    -1.2
scale(len, scale = F)        3.500e-02  5.994e-04    58.4
scale(bigram, scale = F)    -1.285e-02  5.037e-04   -25.5
scale(logitpred, scale = F) -1.992e-02  1.373e-03   -14.5
scale(time, scale = F)      -4.782e-05  1.225e-05    -3.9

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  0.574                                   
scl(bg,s=F)  0.002 -0.275 -0.060                            
scl(lg,s=F)  0.001 -0.309  0.054      -0.250                
scl(tm,s=F) -0.001  0.147  0.125       0.114     -0.068     
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
 140728 140826 -70354   140708  140796
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0294151 0.171508
 sn       (Intercept) 0.0052755 0.072633
 Residual             0.1638152 0.404741
Number of obs: 135274, groups: id, 222; sn, 144

Fixed effects:
                                 Estimate Std. Error t value
(Intercept)                     5.454e+00  1.306e-02   417.8
scale(log_freq, scale = F)      2.287e-03  1.399e-03     1.6
scale(len, scale = F)           3.540e-02  5.990e-04    59.1
scale(bigram, scale = F)       -1.339e-02  5.038e-04   -26.6
scale(logitpred, scale = F)    -2.823e-02  1.436e-03   -19.7
scale(surprisalDep, scale = F)  3.891e-02  1.992e-03    19.5
scale(time, scale = F)         -1.481e-05  1.235e-05    -1.2

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  0.573                                          
scl(bg,s=F)  0.001 -0.280 -0.062                                   
scl(lg,s=F)  0.000 -0.335  0.042      -0.222                       
scl(sD,s=F)  0.004  0.146  0.034      -0.055     -0.296            
scl(tm,s=F)  0.000  0.165  0.128       0.105     -0.104       0.137
[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
 86388 86466 -43186    86372
Random effects:
 Groups Name        Variance Std.Dev.
 id     (Intercept) 0.70577  0.84010 
 sn     (Intercept) 0.10069  0.31732 
Number of obs: 135274, groups: id, 222; sn, 144

Fixed effects:
                                Estimate Std. Error z value Pr(>|z|)    
(Intercept)                    -2.362803   0.063324  -37.31  < 2e-16 ***
scale(log_freq, scale = F)     -0.156043   0.011104  -14.05  < 2e-16 ***
scale(len, scale = F)           0.013907   0.004574    3.04  0.00236 ** 
scale(bigram, scale = F)        0.079308   0.004110   19.30  < 2e-16 ***
scale(logitpred, scale = F)     0.015417   0.011541    1.34  0.18159    
scale(surprisalDep, scale = F)  0.172094   0.015689   10.97  < 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) -0.017 -0.344 -0.072                            
scl(lg,s=F) -0.002 -0.303  0.066      -0.224                
scl(sD,s=F) -0.003  0.132  0.001      -0.088     -0.288     
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
 87520 87598 -43752    87504
Random effects:
 Groups Name        Variance Std.Dev.
 id     (Intercept) 0.076814 0.27715 
 sn     (Intercept) 0.018616 0.13644 
Number of obs: 135274, groups: id, 222; sn, 144

Fixed effects:
                              Estimate Std. Error z value Pr(>|z|)    
(Intercept)                 -2.114e+00  2.394e-02  -88.34  < 2e-16 ***
scale(log_freq, scale = F)  -1.637e-01  1.071e-02  -15.28  < 2e-16 ***
scale(len, scale = F)        5.809e-03  4.395e-03    1.32 0.186234    
scale(bigram, scale = F)     7.380e-02  3.928e-03   18.79  < 2e-16 ***
scale(logitpred, scale = F)  3.765e-02  1.063e-02    3.54 0.000395 ***
scale(time, scale = F)      -6.960e-05  9.495e-05   -0.73 0.463541    
---
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)  0.038                                          
scl(ln,s=F) -0.004  0.536                                   
scl(bg,s=F) -0.042 -0.329 -0.044                            
scl(lg,s=F) -0.004 -0.281  0.069      -0.255                
scl(tm,s=F) -0.001  0.152  0.134       0.103     -0.072     
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
 87262 87351 -43622    87244
Random effects:
 Groups Name        Variance Std.Dev.
 id     (Intercept) 0.087321 0.29550 
 sn     (Intercept) 0.021345 0.14610 
Number of obs: 135274, groups: id, 222; sn, 144

Fixed effects:
                                 Estimate Std. Error z value Pr(>|z|)    
(Intercept)                    -2.140e+00  2.533e-02  -84.50   <2e-16 ***
scale(log_freq, scale = F)     -1.496e-01  1.087e-02  -13.76   <2e-16 ***
scale(len, scale = F)           7.923e-03  4.422e-03    1.79   0.0732 .  
scale(bigram, scale = F)        7.089e-02  3.956e-03   17.92   <2e-16 ***
scale(logitpred, scale = F)     1.082e-02  1.111e-02    0.97   0.3300    
scale(surprisalDep, scale = F)  1.508e-01  1.514e-02    9.96   <2e-16 ***
scale(time, scale = F)          5.595e-05  9.666e-05    0.58   0.5627    
---
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)  0.034                                                 
scl(ln,s=F) -0.004  0.537                                          
scl(bg,s=F) -0.039 -0.337 -0.048                                   
scl(lg,s=F) -0.002 -0.306  0.057      -0.217                       
scl(sD,s=F) -0.009  0.152  0.032      -0.091     -0.283            
scl(tm,s=F) -0.002  0.175  0.137       0.083     -0.103       0.144

> proc.time()
     user    system   elapsed 
20083.271     2.292 20089.713 
