[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
 42741 42827 -21362    42723   42793
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0150503 0.122680
 sn       (Intercept) 0.0014411 0.037962
 Residual             0.0882687 0.297101
Number of obs: 100860, groups: id, 222; sn, 144

Fixed effects:
                                 Estimate Std. Error t value
(Intercept)                     5.2762183  0.0088763   594.4
scale(log_freq, scale = F)      0.0008707  0.0011657     0.7
scale(len, scale = F)           0.0059281  0.0005685    10.4
scale(bigram, scale = F)       -0.0132781  0.0004119   -32.2
scale(logitpred, scale = F)    -0.0136044  0.0011736   -11.6
scale(surprisalDep, scale = F)  0.0392352  0.0017784    22.1

Correlation of Fixed Effects:
            (Intr) s(_s=F scl(ln,s=F) scl(b,s=F) scl(lg,s=F)
scl(l_,s=F) -0.001                                          
scl(ln,s=F) -0.002  0.562                                   
scl(bg,s=F)  0.004 -0.293 -0.068                            
scl(lg,s=F) -0.001 -0.311  0.070      -0.212                
scl(sD,s=F)  0.007  0.130  0.015      -0.068     -0.279     
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
 43023 43109 -21503    43005   43085
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0150177 0.122547
 sn       (Intercept) 0.0012755 0.035715
 Residual             0.0885311 0.297542
Number of obs: 100860, groups: id, 222; sn, 144

Fixed effects:
                              Estimate Std. Error t value
(Intercept)                  5.275e+00  8.803e-03   599.2
scale(log_freq, scale = F)  -1.409e-03  1.159e-03    -1.2
scale(len, scale = F)        6.453e-03  5.706e-04    11.3
scale(bigram, scale = F)    -1.170e-02  4.169e-04   -28.1
scale(logitpred, scale = F) -7.854e-03  1.132e-03    -6.9
scale(time, scale = F)       1.384e-04  9.718e-06    14.2

Correlation of Fixed Effects:
            (Intr) s(_s=F scl(ln,s=F) scl(b,s=F) scl(lg,s=F)
scl(l_,s=F) -0.002                                          
scl(ln,s=F) -0.002  0.567                                   
scl(bg,s=F)  0.004 -0.272 -0.051                            
scl(lg,s=F)  0.001 -0.292  0.069      -0.251                
scl(tm,s=F) -0.002  0.065  0.086       0.165     -0.093     
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
 42462 42557 -21221    42442   42533
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0150179 0.122547
 sn       (Intercept) 0.0014113 0.037568
 Residual             0.0880247 0.296690
Number of obs: 100860, groups: id, 222; sn, 144

Fixed effects:
                                 Estimate Std. Error t value
(Intercept)                     5.276e+00  8.856e-03   595.8
scale(log_freq, scale = F)      2.417e-03  1.168e-03     2.1
scale(len, scale = F)           6.774e-03  5.698e-04    11.9
scale(bigram, scale = F)       -1.217e-02  4.166e-04   -29.2
scale(logitpred, scale = F)    -1.597e-02  1.180e-03   -13.5
scale(surprisalDep, scale = F)  4.248e-02  1.786e-03    23.8
scale(time, scale = F)          1.637e-04  9.754e-06    16.8

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  0.565                                          
scl(bg,s=F)  0.004 -0.276 -0.053                                   
scl(lg,s=F) -0.001 -0.317  0.059      -0.227                       
scl(sD,s=F)  0.006  0.138  0.025      -0.050     -0.289            
scl(tm,s=F) -0.001  0.079  0.088       0.159     -0.120       0.109
[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
 51680 51767 -25831    51662   51733
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0143824 0.119927
 sn       (Intercept) 0.0012299 0.035070
 Residual             0.0872140 0.295320
Number of obs: 126198, groups: id, 222; sn, 144

Fixed effects:
                                 Estimate Std. Error t value
(Intercept)                     5.2731300  0.0086071   612.7
scale(log_freq, scale = F)      0.0061578  0.0010507     5.9
scale(len, scale = F)          -0.0020846  0.0004428    -4.7
scale(bigram, scale = F)       -0.0140083  0.0003816   -36.7
scale(logitpred, scale = F)    -0.0109804  0.0010817   -10.2
scale(surprisalDep, scale = F)  0.0469220  0.0015869    29.6

Correlation of Fixed Effects:
            (Intr) s(_s=F scl(ln,s=F) scl(b,s=F) scl(lg,s=F)
scl(l_,s=F)  0.001                                          
scl(ln,s=F) -0.001  0.545                                   
scl(bg,s=F)  0.001 -0.315 -0.072                            
scl(lg,s=F) -0.001 -0.321  0.060      -0.213                
scl(sD,s=F)  0.005  0.141  0.006      -0.074     -0.294     
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
 52305 52393 -26144    52287   52368
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0143581 0.119825
 sn       (Intercept) 0.0010044 0.031693
 Residual             0.0876672 0.296086
Number of obs: 126198, groups: id, 222; sn, 144

Fixed effects:
                              Estimate Std. Error t value
(Intercept)                  5.272e+00  8.509e-03   619.5
scale(log_freq, scale = F)   2.566e-03  1.042e-03     2.5
scale(len, scale = F)       -1.376e-03  4.454e-04    -3.1
scale(bigram, scale = F)    -1.215e-02  3.867e-04   -31.4
scale(logitpred, scale = F) -3.191e-03  1.040e-03    -3.1
scale(time, scale = F)       1.348e-04  8.637e-06    15.6

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  0.550                                   
scl(bg,s=F)  0.001 -0.296 -0.050                            
scl(lg,s=F)  0.001 -0.298  0.054      -0.258                
scl(tm,s=F) -0.002  0.049  0.108       0.174     -0.100     
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
 51339 51436 -25659    51319   51411
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0143689 0.119871
 sn       (Intercept) 0.0012066 0.034736
 Residual             0.0869785 0.294921
Number of obs: 126198, groups: id, 222; sn, 144

Fixed effects:
                                 Estimate Std. Error t value
(Intercept)                     5.273e+00  8.594e-03   613.6
scale(log_freq, scale = F)      7.358e-03  1.051e-03     7.0
scale(len, scale = F)          -1.179e-03  4.448e-04    -2.7
scale(bigram, scale = F)       -1.281e-02  3.865e-04   -33.1
scale(logitpred, scale = F)    -1.346e-02  1.088e-03   -12.4
scale(surprisalDep, scale = F)  4.968e-02  1.592e-03    31.2
scale(time, scale = F)          1.603e-04  8.650e-06    18.5

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  0.547                                          
scl(bg,s=F)  0.001 -0.300 -0.052                                   
scl(lg,s=F)  0.000 -0.326  0.046      -0.229                       
scl(sD,s=F)  0.005  0.146  0.017      -0.057     -0.302            
scl(tm,s=F) -0.001  0.062  0.109       0.168     -0.123       0.094
[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
 157220 157309 -78601   157202  157269
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0311806 0.176580
 sn       (Intercept) 0.0052623 0.072542
 Residual             0.1851014 0.430234
Number of obs: 135274, groups: id, 222; sn, 144

Fixed effects:
                                 Estimate Std. Error t value
(Intercept)                     5.4724232  0.0133591   409.6
scale(log_freq, scale = F)     -0.0034757  0.0014678    -2.4
scale(len, scale = F)           0.0358431  0.0006310    56.8
scale(bigram, scale = F)       -0.0083673  0.0005321   -15.7
scale(logitpred, scale = F)    -0.0142357  0.0015209    -9.4
scale(surprisalDep, scale = F)  0.0492968  0.0022429    22.0

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  0.562                                   
scl(bg,s=F)  0.001 -0.303 -0.076                            
scl(lg,s=F) -0.001 -0.327  0.058      -0.214                
scl(sD,s=F)  0.005  0.136  0.008      -0.065     -0.294     
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
 157687 157775 -78834   157669  157746
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0311563 0.176512
 sn       (Intercept) 0.0049701 0.070499
 Residual             0.1857533 0.430991
Number of obs: 135274, groups: id, 222; sn, 144

Fixed effects:
                              Estimate Std. Error t value
(Intercept)                  5.471e+00  1.328e-02   412.0
scale(log_freq, scale = F)  -7.570e-03  1.459e-03    -5.2
scale(len, scale = F)        3.599e-02  6.354e-04    56.6
scale(bigram, scale = F)    -7.259e-03  5.395e-04   -13.5
scale(logitpred, scale = F) -4.979e-03  1.463e-03    -3.4
scale(time, scale = F)       4.804e-05  1.214e-05     4.0

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)  0.001 -0.283 -0.056                            
scl(lg,s=F)  0.001 -0.306  0.053      -0.256                
scl(tm,s=F) -0.001  0.056  0.105       0.168     -0.098     
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
 157185 157283 -78583   157165  157253
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0311839 0.176590
 sn       (Intercept) 0.0052362 0.072362
 Residual             0.1850514 0.430176
Number of obs: 135274, groups: id, 222; sn, 144

Fixed effects:
                                 Estimate Std. Error t value
(Intercept)                     5.472e+00  1.335e-02   409.8
scale(log_freq, scale = F)     -2.866e-03  1.471e-03    -1.9
scale(len, scale = F)           3.625e-02  6.346e-04    57.1
scale(bigram, scale = F)       -7.836e-03  5.392e-04   -14.5
scale(logitpred, scale = F)    -1.537e-02  1.532e-03   -10.0
scale(surprisalDep, scale = F)  5.060e-02  2.253e-03    22.5
scale(time, scale = F)          7.410e-05  1.217e-05     6.1

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)  0.000                                                 
scl(ln,s=F) -0.001  0.565                                          
scl(bg,s=F)  0.001 -0.287 -0.057                                   
scl(lg,s=F) -0.001 -0.332  0.045      -0.229                       
scl(sD,s=F)  0.005  0.142  0.018      -0.048     -0.302            
scl(tm,s=F) -0.001  0.068  0.106       0.162     -0.122       0.095
[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
 140722 140810 -70352   140704  140771
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0294153 0.171509
 sn       (Intercept) 0.0052744 0.072625
 Residual             0.1638105 0.404735
Number of obs: 135274, groups: id, 222; sn, 144

Fixed effects:
                                 Estimate Std. Error t value
(Intercept)                     5.4543030  0.0130548   417.8
scale(log_freq, scale = F)      0.0028671  0.0013814     2.1
scale(len, scale = F)           0.0353907  0.0005940    59.6
scale(bigram, scale = F)       -0.0132724  0.0005008   -26.5
scale(logitpred, scale = F)    -0.0287132  0.0014314   -20.1
scale(surprisalDep, scale = F)  0.0422689  0.0021109    20.0

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  0.562                                   
scl(bg,s=F)  0.001 -0.302 -0.076                            
scl(lg,s=F) -0.001 -0.327  0.058      -0.214                
scl(sD,s=F)  0.005  0.137  0.008      -0.065     -0.294     
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
 141106 141194 -70544   141088  141165
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0293972 0.171456
 sn       (Intercept) 0.0050105 0.070785
 Residual             0.1642859 0.405322
Number of obs: 135274, groups: id, 222; sn, 144

Fixed effects:
                              Estimate Std. Error t value
(Intercept)                  5.453e+00  1.298e-02   420.0
scale(log_freq, scale = F)  -6.088e-04  1.372e-03    -0.4
scale(len, scale = F)        3.555e-02  5.980e-04    59.4
scale(bigram, scale = F)    -1.229e-02  5.076e-04   -24.2
scale(logitpred, scale = F) -2.083e-02  1.376e-03   -15.1
scale(time, scale = F)       4.625e-05  1.142e-05     4.1

Correlation of Fixed Effects:
            (Intr) s(_s=F scl(ln,s=F) scl(b,s=F) scl(lg,s=F)
scl(l_,s=F) -0.001                                          
scl(ln,s=F) -0.001  0.568                                   
scl(bg,s=F)  0.001 -0.283 -0.057                            
scl(lg,s=F)  0.001 -0.306  0.053      -0.256                
scl(tm,s=F) -0.001  0.056  0.105       0.168     -0.098     
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
 140688 140786 -70334   140668  140756
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0294175 0.17152 
 sn       (Intercept) 0.0052534 0.07248 
 Residual             0.1637676 0.40468 
Number of obs: 135274, groups: id, 222; sn, 144

Fixed effects:
                                 Estimate Std. Error t value
(Intercept)                     5.454e+00  1.305e-02   418.0
scale(log_freq, scale = F)      3.432e-03  1.384e-03     2.5
scale(len, scale = F)           3.577e-02  5.973e-04    59.9
scale(bigram, scale = F)       -1.278e-02  5.075e-04   -25.2
scale(logitpred, scale = F)    -2.976e-02  1.442e-03   -20.6
scale(surprisalDep, scale = F)  4.347e-02  2.120e-03    20.5
scale(time, scale = F)          6.858e-05  1.145e-05     6.0

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  0.565                                          
scl(bg,s=F)  0.001 -0.287 -0.057                                   
scl(lg,s=F) -0.001 -0.332  0.044      -0.230                       
scl(sD,s=F)  0.005  0.142  0.018      -0.048     -0.302            
scl(tm,s=F) -0.001  0.068  0.106       0.162     -0.122       0.095
[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
 86397 86476 -43191    86381
Random effects:
 Groups Name        Variance Std.Dev.
 id     (Intercept) 0.705652 0.84003 
 sn     (Intercept) 0.099861 0.31601 
Number of obs: 135274, groups: id, 222; sn, 144

Fixed effects:
                                Estimate Std. Error z value Pr(>|z|)    
(Intercept)                    -2.362321   0.063273  -37.34   <2e-16 ***
scale(log_freq, scale = F)     -0.155583   0.011121  -13.99   <2e-16 ***
scale(len, scale = F)           0.013440   0.004574    2.94   0.0033 ** 
scale(bigram, scale = F)        0.079804   0.004109   19.42   <2e-16 ***
scale(logitpred, scale = F)     0.015813   0.011571    1.37   0.1718    
scale(surprisalDep, scale = F)  0.175699   0.016653   10.55   <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  0.535                                   
scl(bg,s=F) -0.017 -0.344 -0.071                            
scl(lg,s=F) -0.002 -0.306  0.068      -0.226                
scl(sD,s=F) -0.002  0.143 -0.008      -0.079     -0.297     
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
 87484 87563 -43734    87468
Random effects:
 Groups Name        Variance Std.Dev.
 id     (Intercept) 0.077654 0.27866 
 sn     (Intercept) 0.020202 0.14214 
Number of obs: 135274, groups: id, 222; sn, 144

Fixed effects:
                              Estimate Std. Error z value Pr(>|z|)    
(Intercept)                 -2.1306864  0.0242548  -87.85  < 2e-16 ***
scale(log_freq, scale = F)  -0.1646491  0.0106356  -15.48  < 2e-16 ***
scale(len, scale = F)        0.0059597  0.0043975    1.36 0.175344    
scale(bigram, scale = F)     0.0738950  0.0039686   18.62  < 2e-16 ***
scale(logitpred, scale = F)  0.0406922  0.0106804    3.81 0.000139 ***
scale(time, scale = F)      -0.0001093  0.0000891   -1.23 0.219931    
---
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  0.530                                   
scl(bg,s=F) -0.042 -0.335 -0.040                            
scl(lg,s=F) -0.005 -0.279  0.066      -0.262                
scl(tm,s=F) -0.001  0.064  0.115       0.156     -0.104     
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
 87476 87564 -43729    87458
Random effects:
 Groups Name        Variance Std.Dev.
 id     (Intercept) 0.072533 0.26932 
 sn     (Intercept) 0.017989 0.13412 
Number of obs: 135274, groups: id, 222; sn, 144

Fixed effects:
                                 Estimate Std. Error z value Pr(>|z|)    
(Intercept)                    -2.115e+00  2.343e-02  -90.28   <2e-16 ***
scale(log_freq, scale = F)     -1.493e-01  1.069e-02  -13.97   <2e-16 ***
scale(len, scale = F)           6.305e-03  4.379e-03    1.44    0.150    
scale(bigram, scale = F)        7.004e-02  3.952e-03   17.72   <2e-16 ***
scale(logitpred, scale = F)     1.012e-02  1.109e-02    0.91    0.362    
scale(surprisalDep, scale = F)  1.494e-01  1.588e-02    9.41   <2e-16 ***
scale(time, scale = F)         -2.025e-05  8.951e-05   -0.23    0.821    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 

Correlation of Fixed Effects:
            (Intr) s(_s=F scl(ln,s=F) scl(b,s=F) scl(lg,s=F) s(Ds=F
scl(l_,s=F)  0.037                                                 
scl(ln,s=F) -0.004  0.528                                          
scl(bg,s=F) -0.041 -0.344 -0.041                                   
scl(lg,s=F) -0.002 -0.303  0.059      -0.223                       
scl(sD,s=F) -0.008  0.147  0.019      -0.079     -0.290            
scl(tm,s=F) -0.002  0.082  0.116       0.141     -0.125       0.116
