[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
 43168 43244 -21576    43152   43211
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0150670 0.122748
 sn       (Intercept) 0.0012606 0.035505
 Residual             0.0887063 0.297836
Number of obs: 100739, groups: id, 222; sn, 144

Fixed effects:
                              Estimate Std. Error t value
(Intercept)                  5.2748284  0.0088098   598.7
scale(log_freq, scale = F)  -0.0024471  0.0011575    -2.1
scale(len, scale = F)        0.0057584  0.0005689    10.1
scale(bigram, scale = F)    -0.0127071  0.0004119   -30.9
scale(logitpred, scale = F) -0.0063880  0.0011285    -5.7

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 -0.288 -0.066                
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
 42837 42922 -21409    42819   42889
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0150602 0.122720
 sn       (Intercept) 0.0014150 0.037616
 Residual             0.0883988 0.297319
Number of obs: 100739, groups: id, 222; sn, 144

Fixed effects:
                                 Estimate Std. Error t value
(Intercept)                     5.2756021  0.0088686   594.9
scale(log_freq, scale = F)     -0.0005115  0.0011615    -0.4
scale(len, scale = F)           0.0059664  0.0005689    10.5
scale(bigram, scale = F)       -0.0128233  0.0004117   -31.2
scale(logitpred, scale = F)    -0.0118308  0.0011660   -10.1
scale(surprisalDep, scale = F)  0.0267125  0.0014596    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) -0.001                                          
scl(ln,s=F) -0.002  0.565                                   
scl(bg,s=F)  0.004 -0.288 -0.067                            
scl(lg,s=F)  0.000 -0.301  0.069      -0.228                
scl(sD,s=F)  0.005  0.091  0.022      -0.017     -0.255     
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
 43162 43248 -21572    43144   43223
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0150742 0.122777
 sn       (Intercept) 0.0012556 0.035435
 Residual             0.0886996 0.297825
Number of obs: 100739, groups: id, 222; sn, 144

Fixed effects:
                              Estimate Std. Error t value
(Intercept)                  5.275e+00  8.810e-03   598.7
scale(log_freq, scale = F)  -3.373e-03  1.203e-03    -2.8
scale(len, scale = F)        5.777e-03  5.689e-04    10.2
scale(bigram, scale = F)    -1.268e-02  4.120e-04   -30.8
scale(logitpred, scale = F) -5.940e-03  1.139e-03    -5.2
scale(time, scale = F)      -4.449e-05  1.577e-05    -2.8

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  0.540                                   
scl(bg,s=F)  0.004 -0.284 -0.066                            
scl(lg,s=F)  0.001 -0.313  0.079      -0.234                
scl(tm,s=F)  0.003  0.273 -0.012      -0.025     -0.139     
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
 42814 42909 -21397    42794   42884
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0150720 0.122768
 sn       (Intercept) 0.0014159 0.037629
 Residual             0.0883771 0.297283
Number of obs: 100739, groups: id, 222; sn, 144

Fixed effects:
                                 Estimate Std. Error t value
(Intercept)                     5.276e+00  8.872e-03   594.6
scale(log_freq, scale = F)     -2.085e-03  1.204e-03    -1.7
scale(len, scale = F)           6.006e-03  5.689e-04    10.6
scale(bigram, scale = F)       -1.278e-02  4.117e-04   -31.0
scale(logitpred, scale = F)    -1.121e-02  1.173e-03    -9.6
scale(surprisalDep, scale = F)  2.755e-02  1.469e-03    18.8
scale(time, scale = F)         -7.849e-05  1.587e-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  0.541                                          
scl(bg,s=F)  0.004 -0.284 -0.067                                   
scl(lg,s=F)  0.000 -0.317  0.070      -0.224                       
scl(sD,s=F)  0.004  0.057  0.023      -0.015     -0.239            
scl(tm,s=F)  0.002  0.264 -0.014      -0.023     -0.107      -0.115
[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
 52463 52541 -26223    52447   52506
Random effects:
 Groups   Name        Variance   Std.Dev.
 id       (Intercept) 0.01438110 0.119921
 sn       (Intercept) 0.00098365 0.031363
 Residual             0.08783131 0.296363
Number of obs: 126018, groups: id, 222; sn, 144

Fixed effects:
                              Estimate Std. Error t value
(Intercept)                  5.2717478  0.0085072   619.7
scale(log_freq, scale = F)   0.0017969  0.0010420     1.7
scale(len, scale = F)       -0.0021159  0.0004431    -4.8
scale(bigram, scale = F)    -0.0132331  0.0003814   -34.7
scale(logitpred, scale = F) -0.0016041  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 -0.310 -0.071                
scl(lg,s=F)  0.001 -0.295  0.065      -0.245    
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
 51756 51843 -25869    51738   51809
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0143866 0.119944
 sn       (Intercept) 0.0012338 0.035126
 Residual             0.0873166 0.295494
Number of obs: 126018, groups: id, 222; sn, 144

Fixed effects:
                                 Estimate Std. Error t value
(Intercept)                     5.2725333  0.0086100   612.4
scale(log_freq, scale = F)      0.0044468  0.0010457     4.3
scale(len, scale = F)          -0.0019663  0.0004431    -4.4
scale(bigram, scale = F)       -0.0133855  0.0003811   -35.1
scale(logitpred, scale = F)    -0.0092863  0.0010739    -8.6
scale(surprisalDep, scale = F)  0.0348362  0.0013038    26.7

Correlation of Fixed Effects:
            (Intr) s(_s=F scl(ln,s=F) scl(b,s=F) scl(lg,s=F)
scl(l_,s=F)  0.000                                          
scl(ln,s=F) -0.001  0.548                                   
scl(bg,s=F)  0.001 -0.309 -0.072                            
scl(lg,s=F)  0.000 -0.309  0.058      -0.232                
scl(sD,s=F)  0.003  0.095  0.016      -0.018     -0.268     
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
 52460 52548 -26221    52442   52522
Random effects:
 Groups   Name        Variance   Std.Dev.
 id       (Intercept) 0.01438244 0.119927
 sn       (Intercept) 0.00097872 0.031284
 Residual             0.08782862 0.296359
Number of obs: 126018, 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)   1.209e-03  1.078e-03     1.1
scale(len, scale = F)       -2.102e-03  4.431e-04    -4.7
scale(bigram, scale = F)    -1.321e-02  3.815e-04   -34.6
scale(logitpred, scale = F) -1.279e-03  1.047e-03    -1.2
scale(time, scale = F)      -2.941e-05  1.389e-05    -2.1

Correlation of Fixed Effects:
            (Intr) s(_s=F scl(ln,s=F) scl(b,s=F) scl(lg,s=F)
scl(l_,s=F)  0.000                                          
scl(ln,s=F) -0.001  0.526                                   
scl(bg,s=F)  0.001 -0.307 -0.070                            
scl(lg,s=F)  0.001 -0.320  0.066      -0.238                
scl(tm,s=F)  0.002  0.258 -0.014      -0.028     -0.147     
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 51824 -25853    51707   51799
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0143898 0.119957
 sn       (Intercept) 0.0012347 0.035138
 Residual             0.0872952 0.295458
Number of obs: 126018, groups: id, 222; sn, 144

Fixed effects:
                                 Estimate Std. Error t value
(Intercept)                     5.272e+00  8.611e-03   612.3
scale(log_freq, scale = F)      2.964e-03  1.079e-03     2.7
scale(len, scale = F)          -1.928e-03  4.432e-04    -4.4
scale(bigram, scale = F)       -1.333e-02  3.812e-04   -35.0
scale(logitpred, scale = F)    -8.629e-03  1.080e-03    -8.0
scale(surprisalDep, scale = F)  3.576e-02  1.314e-03    27.2
scale(time, scale = F)         -7.751e-05  1.400e-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)  0.001                                                 
scl(ln,s=F) -0.001  0.527                                          
scl(bg,s=F)  0.001 -0.306 -0.072                                   
scl(lg,s=F)  0.000 -0.325  0.059      -0.228                       
scl(sD,s=F)  0.003  0.060  0.018      -0.015     -0.250            
scl(tm,s=F)  0.001  0.248 -0.016      -0.025     -0.110      -0.127
[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
 157485 157563 -78734   157469  157525
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0311753 0.176565
 sn       (Intercept) 0.0049662 0.070471
 Residual             0.1857668 0.431007
Number of obs: 135093, groups: id, 222; sn, 144

Fixed effects:
                              Estimate Std. Error t value
(Intercept)                  5.4708628  0.0132814   411.9
scale(log_freq, scale = F)  -0.0078745  0.0014566    -5.4
scale(len, scale = F)        0.0357277  0.0006319    56.5
scale(bigram, scale = F)    -0.0076324  0.0005323   -14.3
scale(logitpred, scale = F) -0.0044320  0.0014562    -3.0

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 -0.298 -0.076                
scl(lg,s=F)  0.001 -0.303  0.063      -0.243    
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
 157224 157312 -78603   157206  157273
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0311933 0.176616
 sn       (Intercept) 0.0052248 0.072283
 Residual             0.1853945 0.430575
Number of obs: 135093, groups: id, 222; sn, 144

Fixed effects:
                                 Estimate Std. Error t value
(Intercept)                     5.4715764  0.0133515   409.8
scale(log_freq, scale = F)     -0.0056900  0.0014616    -3.9
scale(len, scale = F)           0.0359144  0.0006316    56.9
scale(bigram, scale = F)       -0.0077454  0.0005320   -14.6
scale(logitpred, scale = F)    -0.0109523  0.0015094    -7.3
scale(surprisalDep, scale = F)  0.0297812  0.0018341    16.2

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) -0.001  0.565                                   
scl(bg,s=F)  0.002 -0.298 -0.076                            
scl(lg,s=F)  0.000 -0.315  0.056      -0.231                
scl(sD,s=F)  0.003  0.092  0.018      -0.014     -0.266     
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
 157413 157502 -78698   157395  157472
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0311837 0.176589
 sn       (Intercept) 0.0049358 0.070256
 Residual             0.1856667 0.430891
Number of obs: 135093, groups: id, 222; sn, 144

Fixed effects:
                              Estimate Std. Error t value
(Intercept)                  5.471e+00  1.327e-02   412.1
scale(log_freq, scale = F)  -1.125e-02  1.508e-03    -7.5
scale(len, scale = F)        3.580e-02  6.318e-04    56.7
scale(bigram, scale = F)    -7.510e-03  5.324e-04   -14.1
scale(logitpred, scale = F) -2.638e-03  1.471e-03    -1.8
scale(time, scale = F)      -1.692e-04  1.975e-05    -8.6

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  0.543                                   
scl(bg,s=F)  0.002 -0.294 -0.075                            
scl(lg,s=F)  0.001 -0.327  0.065      -0.237                
scl(tm,s=F)  0.002  0.261 -0.013      -0.027     -0.142     
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
 157111 157209 -78545   157091  157177
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0312030 0.176644
 sn       (Intercept) 0.0052268 0.072297
 Residual             0.1852360 0.430391
Number of obs: 135093, groups: id, 222; sn, 144

Fixed effects:
                                 Estimate Std. Error t value
(Intercept)                     5.471e+00  1.335e-02   409.7
scale(log_freq, scale = F)     -9.764e-03  1.509e-03    -6.5
scale(len, scale = F)           3.602e-02  6.314e-04    57.0
scale(bigram, scale = F)       -7.601e-03  5.319e-04   -14.3
scale(logitpred, scale = F)    -9.241e-03  1.517e-03    -6.1
scale(surprisalDep, scale = F)  3.230e-02  1.848e-03    17.5
scale(time, scale = F)         -2.134e-04  1.989e-05   -10.7

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)  0.000                                                 
scl(ln,s=F) -0.001  0.543                                          
scl(bg,s=F)  0.002 -0.294 -0.076                                   
scl(lg,s=F)  0.000 -0.330  0.058      -0.227                       
scl(sD,s=F)  0.003  0.056  0.020      -0.011     -0.249            
scl(tm,s=F)  0.001  0.252 -0.015      -0.025     -0.105      -0.127
[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
 140926 141004 -70455   140910  140966
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0294115 0.171498
 sn       (Intercept) 0.0050363 0.070967
 Residual             0.1642960 0.405334
Number of obs: 135093, groups: id, 222; sn, 144

Fixed effects:
                              Estimate Std. Error t value
(Intercept)                  5.4530520  0.0129907   419.8
scale(log_freq, scale = F)  -0.0009561  0.0013705    -0.7
scale(len, scale = F)        0.0352875  0.0005948    59.3
scale(bigram, scale = F)    -0.0126006  0.0005009   -25.2
scale(logitpred, scale = F) -0.0202528  0.0013701   -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      -0.244    
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
 140754 140842 -70368   140736  140803
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0294235 0.171533
 sn       (Intercept) 0.0052529 0.072477
 Residual             0.1640771 0.405064
Number of obs: 135093, groups: id, 222; sn, 144

Fixed effects:
                                 Estimate Std. Error t value
(Intercept)                     5.4535997  0.0130514   417.9
scale(log_freq, scale = F)      0.0007134  0.0013756     0.5
scale(len, scale = F)           0.0354273  0.0005946    59.6
scale(bigram, scale = F)       -0.0126858  0.0005007   -25.3
scale(logitpred, scale = F)    -0.0252417  0.0014207   -17.8
scale(surprisalDep, scale = F)  0.0227675  0.0017262    13.2

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) -0.001  0.565                                   
scl(bg,s=F)  0.002 -0.297 -0.076                            
scl(lg,s=F)  0.000 -0.315  0.056      -0.231                
scl(sD,s=F)  0.003  0.092  0.018      -0.014     -0.266     
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
 140829 140917 -70406   140811  140888
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0294194 0.171521
 sn       (Intercept) 0.0049874 0.070622
 Residual             0.1641777 0.405188
Number of obs: 135093, 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)  -4.636e-03  1.419e-03    -3.3
scale(len, scale = F)        3.536e-02  5.946e-04    59.5
scale(bigram, scale = F)    -1.247e-02  5.009e-04   -24.9
scale(logitpred, scale = F) -1.830e-02  1.384e-03   -13.2
scale(time, scale = F)      -1.843e-04  1.858e-05    -9.9

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  0.543                                   
scl(bg,s=F)  0.002 -0.294 -0.076                            
scl(lg,s=F)  0.001 -0.327  0.064      -0.237                
scl(tm,s=F)  0.002  0.261 -0.013      -0.027     -0.142     
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
 140619 140717 -70299   140599  140687
Random effects:
 Groups   Name        Variance Std.Dev.
 id       (Intercept) 0.029434 0.171564
 sn       (Intercept) 0.005234 0.072347
 Residual             0.163911 0.404859
Number of obs: 135093, groups: id, 222; sn, 144

Fixed effects:
                                 Estimate Std. Error t value
(Intercept)                     5.453e+00  1.305e-02   418.0
scale(log_freq, scale = F)     -3.470e-03  1.421e-03    -2.4
scale(len, scale = F)           3.553e-02  5.944e-04    59.8
scale(bigram, scale = F)       -1.254e-02  5.006e-04   -25.1
scale(logitpred, scale = F)    -2.348e-02  1.428e-03   -16.4
scale(surprisalDep, scale = F)  2.536e-02  1.739e-03    14.6
scale(time, scale = F)         -2.190e-04  1.872e-05   -11.7

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)  0.000                                                 
scl(ln,s=F) -0.001  0.543                                          
scl(bg,s=F)  0.002 -0.294 -0.076                                   
scl(lg,s=F)  0.000 -0.330  0.058      -0.227                       
scl(sD,s=F)  0.003  0.056  0.020      -0.011     -0.249            
scl(tm,s=F)  0.001  0.252 -0.015      -0.025     -0.105      -0.127
[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
 86339 86408 -43162    86325
Random effects:
 Groups Name        Variance Std.Dev.
 id     (Intercept) 0.703949 0.83902 
 sn     (Intercept) 0.098844 0.31440 
Number of obs: 135093, groups: id, 222; sn, 144

Fixed effects:
                             Estimate Std. Error z value Pr(>|z|)    
(Intercept)                 -2.364664   0.063157  -37.44  < 2e-16 ***
scale(log_freq, scale = F)  -0.171859   0.011041  -15.56  < 2e-16 ***
scale(len, scale = F)        0.013927   0.004572    3.05  0.00232 ** 
scale(bigram, scale = F)     0.082926   0.004110   20.18  < 2e-16 ***
scale(logitpred, scale = F)  0.051653   0.011066    4.67 3.05e-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 -0.284  0.069      -0.262    
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
 86257 86335 -43120    86241
Random effects:
 Groups Name        Variance Std.Dev.
 id     (Intercept) 0.70495  0.83961 
 sn     (Intercept) 0.10055  0.31710 
Number of obs: 135093, groups: id, 222; sn, 144

Fixed effects:
                                Estimate Std. Error z value Pr(>|z|)    
(Intercept)                    -2.364461   0.063288  -37.36  < 2e-16 ***
scale(log_freq, scale = F)     -0.162034   0.011059  -14.65  < 2e-16 ***
scale(len, scale = F)           0.014028   0.004572    3.07  0.00215 ** 
scale(bigram, scale = F)        0.082155   0.004111   19.99  < 2e-16 ***
scale(logitpred, scale = F)     0.022498   0.011500    1.96  0.05042 .  
scale(surprisalDep, scale = F)  0.128957   0.014039    9.19  < 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) -0.004  0.538                                   
scl(bg,s=F) -0.018 -0.338 -0.071                            
scl(lg,s=F) -0.001 -0.293  0.065      -0.247                
scl(sD,s=F) -0.004  0.094  0.002      -0.021     -0.272     
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
 86431 86509 -43207    86415
Random effects:
 Groups Name        Variance Std.Dev.
 id     (Intercept) 0.383380 0.61918 
 sn     (Intercept) 0.046304 0.21518 
Number of obs: 135093, groups: id, 222; sn, 144

Fixed effects:
                              Estimate Std. Error z value Pr(>|z|)    
(Intercept)                 -2.189e+00  4.658e-02  -47.00  < 2e-16 ***
scale(log_freq, scale = F)  -1.730e-01  1.128e-02  -15.34  < 2e-16 ***
scale(len, scale = F)        7.712e-03  4.505e-03    1.71   0.0869 .  
scale(bigram, scale = F)     7.528e-02  4.050e-03   18.59  < 2e-16 ***
scale(logitpred, scale = F)  4.749e-02  1.103e-02    4.31 1.65e-05 ***
scale(time, scale = F)      -6.478e-05  1.430e-04   -0.45   0.6505    
---
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)  0.021                                          
scl(ln,s=F) -0.003  0.512                                   
scl(bg,s=F) -0.022 -0.342 -0.066                            
scl(lg,s=F) -0.003 -0.305  0.074      -0.247                
scl(tm,s=F)  0.004  0.262 -0.013      -0.049     -0.136     
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
 86392 86480 -43187    86374
Random effects:
 Groups Name        Variance Std.Dev.
 id     (Intercept) 0.278048 0.5273  
 sn     (Intercept) 0.063657 0.2523  
Number of obs: 135093, groups: id, 222; sn, 144

Fixed effects:
                                 Estimate Std. Error z value Pr(>|z|)    
(Intercept)                    -2.1652537  0.0425737  -50.86   <2e-16 ***
scale(log_freq, scale = F)     -0.1745835  0.0113506  -15.38   <2e-16 ***
scale(len, scale = F)           0.0100191  0.0045254    2.21   0.0268 *  
scale(bigram, scale = F)        0.0889087  0.0040740   21.82   <2e-16 ***
scale(logitpred, scale = F)     0.0146089  0.0114426    1.28   0.2017    
scale(surprisalDep, scale = F)  0.1265567  0.0139757    9.06   <2e-16 ***
scale(time, scale = F)         -0.0002228  0.0001444   -1.54   0.1229    
---
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)  0.024                                                 
scl(ln,s=F) -0.004  0.514                                          
scl(bg,s=F) -0.029 -0.345 -0.067                                   
scl(lg,s=F) -0.001 -0.304  0.067      -0.239                       
scl(sD,s=F) -0.006  0.058  0.007      -0.018     -0.253            
scl(tm,s=F)  0.005  0.255 -0.013      -0.046     -0.096      -0.123
