[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
 33187 33261 -16585    33171   33229
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0151177 0.122954
 sn       (Intercept) 0.0020622 0.045411
 Residual             0.0866056 0.294288
Number of obs: 81417, groups: id, 222; sn, 144

Fixed effects:
                              Estimate Std. Error t value
(Intercept)                  5.2745321  0.0091460   576.7
scale(log_freq, scale = F)  -0.0037670  0.0013129    -2.9
scale(len, scale = F)        0.0061758  0.0006287     9.8
scale(bigram, scale = F)    -0.0132027  0.0004736   -27.9
scale(logitpred, scale = F) -0.0043680  0.0012890    -3.4

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  0.533                       
scl(bg,s=F)  0.004 -0.307 -0.085                
scl(lg,s=F)  0.002 -0.241  0.101      -0.312    
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
 33159 33243 -16571    33141   33211
Random effects:
 Groups   Name        Variance Std.Dev.
 id       (Intercept) 0.015115 0.122945
 sn       (Intercept) 0.002121 0.046054
 Residual             0.086570 0.294227
Number of obs: 81417, groups: id, 222; sn, 144

Fixed effects:
                                 Estimate Std. Error t value
(Intercept)                     5.2746887  0.0091677   575.4
scale(log_freq, scale = F)     -0.0032408  0.0013165    -2.5
scale(len, scale = F)           0.0059897  0.0006297     9.5
scale(bigram, scale = F)       -0.0131855  0.0004736   -27.8
scale(logitpred, scale = F)    -0.0058919  0.0013187    -4.5
scale(surprisalDep, scale = F)  0.0058228  0.0010639     5.5

Correlation of Fixed Effects:
            (Intr) s(_s=F scl(ln,s=F) scl(b,s=F) scl(lg,s=F)
scl(l_,s=F) -0.001                                          
scl(ln,s=F) -0.002  0.527                                   
scl(bg,s=F)  0.004 -0.305 -0.085                            
scl(lg,s=F)  0.001 -0.250  0.109      -0.306                
scl(sD,s=F)  0.003  0.073 -0.053       0.005     -0.211     
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
 33147 33231 -16564    33129   33207
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0151267 0.122991
 sn       (Intercept) 0.0020459 0.045232
 Residual             0.0865615 0.294213
Number of obs: 81417, groups: id, 222; sn, 144

Fixed effects:
                              Estimate Std. Error t value
(Intercept)                  5.275e+00  9.142e-03   577.0
scale(log_freq, scale = F)  -6.475e-03  1.377e-03    -4.7
scale(len, scale = F)        6.316e-03  6.289e-04    10.0
scale(bigram, scale = F)    -1.317e-02  4.735e-04   -27.8
scale(logitpred, scale = F) -3.127e-03  1.303e-03    -2.4
scale(time, scale = F)      -8.965e-05  1.380e-05    -6.5

Correlation of Fixed Effects:
            (Intr) s(_s=F scl(ln,s=F) scl(b,s=F) scl(lg,s=F)
scl(l_,s=F) -0.002                                          
scl(ln,s=F) -0.001  0.497                                   
scl(bg,s=F)  0.004 -0.295 -0.084                            
scl(lg,s=F)  0.002 -0.271  0.105      -0.307                
scl(tm,s=F) -0.003  0.303 -0.034      -0.010     -0.147     
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
 33048 33141 -16514    33028   33118
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0151305 0.123006
 sn       (Intercept) 0.0021764 0.046652
 Residual             0.0864453 0.294016
Number of obs: 81417, groups: id, 222; sn, 144

Fixed effects:
                                 Estimate Std. Error t value
(Intercept)                     5.2752152  0.0091924   573.9
scale(log_freq, scale = F)     -0.0077595  0.0013829    -5.6
scale(len, scale = F)           0.0060455  0.0006296     9.6
scale(bigram, scale = F)       -0.0131116  0.0004734   -27.7
scale(logitpred, scale = F)    -0.0052508  0.0013195    -4.0
scale(surprisalDep, scale = F)  0.0123101  0.0012256    10.0
scale(time, scale = F)         -0.0001691  0.0000159   -10.6

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) -0.002                                                 
scl(ln,s=F) -0.002  0.499                                          
scl(bg,s=F)  0.004 -0.295 -0.085                                   
scl(lg,s=F)  0.001 -0.252  0.110      -0.305                       
scl(sD,s=F)  0.005 -0.093 -0.042       0.011     -0.160            
scl(tm,s=F) -0.005  0.307 -0.009      -0.014     -0.046      -0.497
[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
 42708 42784 -21346    42692   42751
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0143519 0.119799
 sn       (Intercept) 0.0017634 0.041993
 Residual             0.0874419 0.295706
Number of obs: 103080, groups: id, 222; sn, 144

Fixed effects:
                              Estimate Std. Error t value
(Intercept)                  5.269e+00  8.823e-03   597.1
scale(log_freq, scale = F)   2.895e-04  1.196e-03     0.2
scale(len, scale = F)       -1.796e-03  4.898e-04    -3.7
scale(bigram, scale = F)    -1.331e-02  4.395e-04   -30.3
scale(logitpred, scale = F)  9.156e-05  1.190e-03     0.1

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)  0.000  0.513                       
scl(bg,s=F)  0.001 -0.328 -0.089                
scl(lg,s=F)  0.001 -0.250  0.084      -0.311    
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
 42626 42712 -21304    42608   42679
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0143553 0.119814
 sn       (Intercept) 0.0018699 0.043243
 Residual             0.0873637 0.295574
Number of obs: 103080, groups: id, 222; sn, 144

Fixed effects:
                                 Estimate Std. Error t value
(Intercept)                     5.2686463  0.0088668   594.2
scale(log_freq, scale = F)      0.0010267  0.0011990     0.9
scale(len, scale = F)          -0.0020293  0.0004906    -4.1
scale(bigram, scale = F)       -0.0133018  0.0004395   -30.3
scale(logitpred, scale = F)    -0.0022033  0.0012161    -1.8
scale(surprisalDep, scale = F)  0.0087533  0.0009534     9.2

Correlation of Fixed Effects:
            (Intr) s(_s=F scl(ln,s=F) scl(b,s=F) scl(lg,s=F)
scl(l_,s=F)  0.000                                          
scl(ln,s=F)  0.000  0.508                                   
scl(bg,s=F)  0.001 -0.327 -0.089                            
scl(lg,s=F)  0.001 -0.258  0.092      -0.305                
scl(sD,s=F)  0.001  0.067 -0.050      -0.001     -0.206     
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
 42687 42773 -21334    42669   42748
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0143518 0.119799
 sn       (Intercept) 0.0017509 0.041844
 Residual             0.0874230 0.295674
Number of obs: 103080, groups: id, 222; sn, 144

Fixed effects:
                              Estimate Std. Error t value
(Intercept)                  5.269e+00  8.818e-03   597.5
scale(log_freq, scale = F)  -1.447e-03  1.249e-03    -1.2
scale(len, scale = F)       -1.739e-03  4.898e-04    -3.5
scale(bigram, scale = F)    -1.327e-02  4.395e-04   -30.2
scale(logitpred, scale = F)  8.983e-04  1.202e-03     0.7
scale(time, scale = F)      -5.912e-05  1.227e-05    -4.8

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)  0.001  0.484                                   
scl(bg,s=F)  0.001 -0.319 -0.088                            
scl(lg,s=F)  0.002 -0.277  0.087      -0.306                
scl(tm,s=F) -0.004  0.288 -0.024      -0.017     -0.139     
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
 42512 42608 -21246    42492   42584
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0143588 0.119828
 sn       (Intercept) 0.0019307 0.043940
 Residual             0.0872617 0.295401
Number of obs: 103080, groups: id, 222; sn, 144

Fixed effects:
                                 Estimate Std. Error t value
(Intercept)                     5.269e+00  8.890e-03   592.7
scale(log_freq, scale = F)     -2.942e-03  1.254e-03    -2.3
scale(len, scale = F)          -2.040e-03  4.905e-04    -4.2
scale(bigram, scale = F)       -1.321e-02  4.394e-04   -30.1
scale(logitpred, scale = F)    -1.664e-03  1.217e-03    -1.4
scale(surprisalDep, scale = F)  1.460e-02  1.096e-03    13.3
scale(time, scale = F)         -1.519e-04  1.412e-05   -10.8

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)  0.000  0.486                                          
scl(bg,s=F)  0.001 -0.318 -0.089                                   
scl(lg,s=F)  0.001 -0.259  0.092      -0.304                       
scl(sD,s=F)  0.003 -0.090 -0.044       0.009     -0.158            
scl(tm,s=F) -0.005  0.294  0.001      -0.019     -0.042      -0.494
[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
 126792 126869 -63388   126776  126831
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0312090 0.17666 
 sn       (Intercept) 0.0069423 0.08332 
 Residual             0.1836503 0.42854 
Number of obs: 109621, groups: id, 222; sn, 144

Fixed effects:
                              Estimate Std. Error t value
(Intercept)                  5.4700936  0.0138076   396.2
scale(log_freq, scale = F)  -0.0114450  0.0016667    -6.9
scale(len, scale = F)        0.0374465  0.0006959    53.8
scale(bigram, scale = F)    -0.0068704  0.0006120   -11.2
scale(logitpred, scale = F) -0.0011562  0.0016730    -0.7

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)  0.000  0.531                       
scl(bg,s=F)  0.002 -0.317 -0.093                
scl(lg,s=F)  0.001 -0.256  0.084      -0.311    
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
 126781 126867 -63381   126763  126829
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0312125 0.176670
 sn       (Intercept) 0.0070176 0.083771
 Residual             0.1836255 0.428515
Number of obs: 109621, groups: id, 222; sn, 144

Fixed effects:
                                 Estimate Std. Error t value
(Intercept)                     5.4701404  0.0138271   395.6
scale(log_freq, scale = F)     -0.0110431  0.0016703    -6.6
scale(len, scale = F)           0.0373220  0.0006967    53.6
scale(bigram, scale = F)       -0.0068608  0.0006120   -11.2
scale(logitpred, scale = F)    -0.0024234  0.0017089    -1.4
scale(surprisalDep, scale = F)  0.0049204  0.0013516     3.6

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)  0.000  0.526                                   
scl(bg,s=F)  0.002 -0.316 -0.093                            
scl(lg,s=F)  0.001 -0.264  0.092      -0.306                
scl(sD,s=F)  0.001  0.065 -0.050       0.004     -0.204     
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
 126683 126770 -63333   126665  126740
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0312142 0.176675
 sn       (Intercept) 0.0067315 0.082046
 Residual             0.1834711 0.428335
Number of obs: 109621, groups: id, 222; sn, 144

Fixed effects:
                              Estimate Std. Error t value
(Intercept)                  5.471e+00  1.376e-02   397.7
scale(log_freq, scale = F)  -1.681e-02  1.741e-03    -9.7
scale(len, scale = F)        3.762e-02  6.956e-04    54.1
scale(bigram, scale = F)    -6.779e-03  6.117e-04   -11.1
scale(logitpred, scale = F)  1.296e-03  1.688e-03     0.8
scale(time, scale = F)      -1.839e-04  1.746e-05   -10.5

Correlation of Fixed Effects:
            (Intr) s(_s=F scl(ln,s=F) scl(b,s=F) scl(lg,s=F)
scl(l_,s=F) -0.001                                          
scl(ln,s=F)  0.000  0.501                                   
scl(bg,s=F)  0.002 -0.308 -0.093                            
scl(lg,s=F)  0.002 -0.283  0.087      -0.306                
scl(tm,s=F) -0.004  0.292 -0.024      -0.015     -0.138     
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
 126580 126677 -63280   126560  126647
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0312247 0.176705
 sn       (Intercept) 0.0069031 0.083085
 Residual             0.1832893 0.428123
Number of obs: 109621, groups: id, 222; sn, 144

Fixed effects:
                                 Estimate Std. Error t value
(Intercept)                     5.471e+00  1.380e-02   396.4
scale(log_freq, scale = F)     -1.849e-02  1.749e-03   -10.6
scale(len, scale = F)           3.731e-02  6.960e-04    53.6
scale(bigram, scale = F)       -6.696e-03  6.115e-04   -11.0
scale(logitpred, scale = F)    -1.441e-03  1.709e-03    -0.8
scale(surprisalDep, scale = F)  1.594e-02  1.557e-03    10.2
scale(time, scale = F)         -2.864e-04  2.012e-05   -14.2

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) -0.001                                                 
scl(ln,s=F)  0.000  0.502                                          
scl(bg,s=F)  0.002 -0.308 -0.093                                   
scl(lg,s=F)  0.001 -0.264  0.092      -0.304                       
scl(sD,s=F)  0.003 -0.095 -0.043       0.013     -0.157            
scl(tm,s=F) -0.005  0.299  0.001      -0.019     -0.040      -0.498
[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
 113460 113537 -56722   113444  113500
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0291275 0.170668
 sn       (Intercept) 0.0069832 0.083566
 Residual             0.1625764 0.403208
Number of obs: 109621, groups: id, 222; sn, 144

Fixed effects:
                              Estimate Std. Error t value
(Intercept)                  5.4526464  0.0134672   404.9
scale(log_freq, scale = F)  -0.0046728  0.0015692    -3.0
scale(len, scale = F)        0.0363603  0.0006553    55.5
scale(bigram, scale = F)    -0.0126525  0.0005761   -22.0
scale(logitpred, scale = F) -0.0164916  0.0015749   -10.5

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)  0.000  0.532                       
scl(bg,s=F)  0.002 -0.317 -0.093                
scl(lg,s=F)  0.001 -0.257  0.084      -0.312    
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
 113456 113543 -56719   113438  113505
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0291285 0.170671
 sn       (Intercept) 0.0070374 0.083889
 Residual             0.1625659 0.403195
Number of obs: 109621, groups: id, 222; sn, 144

Fixed effects:
                                 Estimate Std. Error t value
(Intercept)                     5.4526759  0.0134805   404.5
scale(log_freq, scale = F)     -0.0044191  0.0015725    -2.8
scale(len, scale = F)           0.0362806  0.0006562    55.3
scale(bigram, scale = F)       -0.0126461  0.0005761   -22.0
scale(logitpred, scale = F)    -0.0172939  0.0016088   -10.7
scale(surprisalDep, scale = F)  0.0031106  0.0012727     2.4

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)  0.000  0.526                                   
scl(bg,s=F)  0.002 -0.316 -0.093                            
scl(lg,s=F)  0.001 -0.264  0.092      -0.306                
scl(sD,s=F)  0.001  0.065 -0.050       0.004     -0.204     
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
 113330 113417 -56656   113312  113388
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0291327 0.170683
 sn       (Intercept) 0.0067774 0.082325
 Residual             0.1623864 0.402972
Number of obs: 109621, groups: id, 222; sn, 144

Fixed effects:
                              Estimate Std. Error t value
(Intercept)                  5.453e+00  1.341e-02   406.5
scale(log_freq, scale = F)  -1.018e-02  1.639e-03    -6.2
scale(len, scale = F)        3.654e-02  6.550e-04    55.8
scale(bigram, scale = F)    -1.256e-02  5.757e-04   -21.8
scale(logitpred, scale = F) -1.397e-02  1.589e-03    -8.8
scale(time, scale = F)      -1.889e-04  1.644e-05   -11.5

Correlation of Fixed Effects:
            (Intr) s(_s=F scl(ln,s=F) scl(b,s=F) scl(lg,s=F)
scl(l_,s=F) -0.001                                          
scl(ln,s=F)  0.000  0.501                                   
scl(bg,s=F)  0.002 -0.308 -0.093                            
scl(lg,s=F)  0.001 -0.283  0.087      -0.306                
scl(tm,s=F) -0.004  0.292 -0.024      -0.015     -0.138     
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
 113244 113340 -56612   113224  113311
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0291411 0.17071 
 sn       (Intercept) 0.0069589 0.08342 
 Residual             0.1622492 0.40280 
Number of obs: 109621, groups: id, 222; sn, 144

Fixed effects:
                                 Estimate Std. Error t value
(Intercept)                     5.454e+00  1.346e-02   405.1
scale(log_freq, scale = F)     -1.164e-02  1.646e-03    -7.1
scale(len, scale = F)           3.627e-02  6.555e-04    55.3
scale(bigram, scale = F)       -1.249e-02  5.756e-04   -21.7
scale(logitpred, scale = F)    -1.635e-02  1.608e-03   -10.2
scale(surprisalDep, scale = F)  1.380e-02  1.466e-03     9.4
scale(time, scale = F)         -2.776e-04  1.895e-05   -14.7

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)  0.000  0.503                                          
scl(bg,s=F)  0.002 -0.307 -0.093                                   
scl(lg,s=F)  0.001 -0.264  0.092      -0.305                       
scl(sD,s=F)  0.003 -0.095 -0.044       0.013     -0.157            
scl(tm,s=F) -0.005  0.299  0.001      -0.019     -0.040      -0.498
[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
 69961 70028 -34974    69947
Random effects:
 Groups Name        Variance Std.Dev.
 id     (Intercept) 0.71016  0.84271 
 sn     (Intercept) 0.10635  0.32611 
Number of obs: 109621, groups: id, 222; sn, 144

Fixed effects:
                             Estimate Std. Error z value Pr(>|z|)    
(Intercept)                 -2.378145   0.064052  -37.13  < 2e-16 ***
scale(log_freq, scale = F)  -0.194364   0.012853  -15.12  < 2e-16 ***
scale(len, scale = F)        0.014068   0.005032    2.80 0.005179 ** 
scale(bigram, scale = F)     0.095860   0.004757   20.15  < 2e-16 ***
scale(logitpred, scale = F)  0.047833   0.012746    3.75 0.000175 ***
---
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)  0.019                              
scl(ln,s=F) -0.003  0.498                       
scl(bg,s=F) -0.022 -0.374 -0.091                
scl(lg,s=F) -0.002 -0.235  0.087      -0.326    
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
 69949 70026 -34967    69933
Random effects:
 Groups Name        Variance Std.Dev.
 id     (Intercept) 0.71049  0.84290 
 sn     (Intercept) 0.10836  0.32917 
Number of obs: 109621, groups: id, 222; sn, 144

Fixed effects:
                                Estimate Std. Error z value Pr(>|z|)    
(Intercept)                    -2.378725   0.064179  -37.06  < 2e-16 ***
scale(log_freq, scale = F)     -0.191735   0.012858  -14.91  < 2e-16 ***
scale(len, scale = F)           0.012990   0.005042    2.58 0.009989 ** 
scale(bigram, scale = F)        0.095898   0.004758   20.15  < 2e-16 ***
scale(logitpred, scale = F)     0.038499   0.012982    2.97 0.003022 ** 
scale(surprisalDep, scale = F)  0.038893   0.010359    3.75 0.000174 ***
---
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)  0.019                                          
scl(ln,s=F) -0.002  0.494                                   
scl(bg,s=F) -0.022 -0.373 -0.091                            
scl(lg,s=F) -0.001 -0.239  0.097      -0.320                
scl(sD,s=F) -0.004  0.053 -0.058       0.004     -0.194     
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
 70384 70461 -35184    70368
Random effects:
 Groups Name        Variance Std.Dev.
 id     (Intercept) 0.137714 0.37110 
 sn     (Intercept) 0.057475 0.23974 
Number of obs: 109621, groups: id, 222; sn, 144

Fixed effects:
                              Estimate Std. Error z value Pr(>|z|)    
(Intercept)                 -2.134e+00  3.396e-02  -62.83  < 2e-16 ***
scale(log_freq, scale = F)  -1.919e-01  1.310e-02  -14.65  < 2e-16 ***
scale(len, scale = F)        2.590e-04  4.934e-03    0.05  0.95813    
scale(bigram, scale = F)     9.121e-02  4.648e-03   19.62  < 2e-16 ***
scale(logitpred, scale = F)  3.541e-02  1.258e-02    2.81  0.00489 ** 
scale(time, scale = F)       5.235e-05  1.281e-04    0.41  0.68284    
---
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)  0.031                                          
scl(ln,s=F)  0.001  0.465                                   
scl(bg,s=F) -0.039 -0.367 -0.086                            
scl(lg,s=F)  0.000 -0.261  0.091      -0.316                
scl(tm,s=F) -0.011  0.291 -0.019      -0.028     -0.138     
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
 70343 70429 -35162    70325
Random effects:
 Groups Name        Variance Std.Dev.
 id     (Intercept) 0.152221 0.39015 
 sn     (Intercept) 0.040241 0.20060 
Number of obs: 109621, groups: id, 222; sn, 144

Fixed effects:
                                 Estimate Std. Error z value Pr(>|z|)    
(Intercept)                    -2.1483075  0.0331565  -64.79  < 2e-16 ***
scale(log_freq, scale = F)     -0.1975074  0.0130669  -15.12  < 2e-16 ***
scale(len, scale = F)           0.0064848  0.0048715    1.33 0.183129    
scale(bigram, scale = F)        0.0927631  0.0046218   20.07  < 2e-16 ***
scale(logitpred, scale = F)     0.0315408  0.0125868    2.51 0.012215 *  
scale(surprisalDep, scale = F)  0.0394327  0.0113952    3.46 0.000539 ***
scale(time, scale = F)         -0.0002378  0.0001450   -1.64 0.101072    
---
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)  0.033                                                 
scl(ln,s=F) -0.001  0.463                                          
scl(bg,s=F) -0.041 -0.372 -0.081                                   
scl(lg,s=F) -0.001 -0.238  0.098      -0.310                       
scl(sD,s=F)  0.000 -0.100 -0.043       0.006     -0.138            
scl(tm,s=F) -0.008  0.300  0.006      -0.028     -0.049      -0.487
