[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
 42786 42871 -21384    42768   42837
Random effects:
 Groups   Name        Variance Std.Dev.
 id       (Intercept) 0.015047 0.122667
 sn       (Intercept) 0.001433 0.037855
 Residual             0.088308 0.297167
Number of obs: 100860, groups: id, 222; sn, 144

Fixed effects:
                                 Estimate Std. Error t value
(Intercept)                     5.2760624  0.0088724   594.7
scale(log_freq, scale = F)      0.0001706  0.0011628     0.1
scale(len, scale = F)           0.0059977  0.0005687    10.5
scale(bigram, scale = F)       -0.0131682  0.0004118   -32.0
scale(logitpred, scale = F)    -0.0130469  0.0011709   -11.1
scale(surprisalDep, scale = F)  0.0340079  0.0016176    21.0

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) -0.002  0.564                                   
scl(bg,s=F)  0.004 -0.291 -0.068                            
scl(lg,s=F) -0.001 -0.305  0.069      -0.216                
scl(sD,s=F)  0.006  0.109  0.022      -0.059     -0.271     
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
 43197 43283 -21590    43179   43259
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0150333 0.122610
 sn       (Intercept) 0.0012664 0.035587
 Residual             0.0886853 0.297801
Number of obs: 100860, groups: id, 222; sn, 144

Fixed effects:
                              Estimate Std. Error t value
(Intercept)                  5.275e+00  8.804e-03   599.2
scale(log_freq, scale = F)  -1.111e-03  1.185e-03    -0.9
scale(len, scale = F)        6.085e-03  5.722e-04    10.6
scale(bigram, scale = F)    -1.245e-02  4.136e-04   -30.1
scale(logitpred, scale = F) -6.759e-03  1.131e-03    -6.0
scale(time, scale = F)       5.705e-05  1.070e-05     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) -0.002                                          
scl(ln,s=F) -0.002  0.572                                   
scl(bg,s=F)  0.004 -0.257 -0.055                            
scl(lg,s=F)  0.001 -0.295  0.070      -0.245                
scl(tm,s=F) -0.001  0.217  0.108       0.101     -0.066     
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
 42723 42819 -21352    42703   42794
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0150294 0.122594
 sn       (Intercept) 0.0014163 0.037633
 Residual             0.0882535 0.297075
Number of obs: 100860, groups: id, 222; sn, 144

Fixed effects:
                                 Estimate Std. Error t value
(Intercept)                     5.276e+00  8.861e-03   595.4
scale(log_freq, scale = F)      2.375e-03  1.194e-03     2.0
scale(len, scale = F)           6.511e-03  5.720e-04    11.4
scale(bigram, scale = F)       -1.286e-02  4.135e-04   -31.1
scale(logitpred, scale = F)    -1.397e-02  1.176e-03   -11.9
scale(surprisalDep, scale = F)  3.563e-02  1.630e-03    21.9
scale(time, scale = F)          8.636e-05  1.076e-05     8.0

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) -0.001                                                 
scl(ln,s=F) -0.002  0.571                                          
scl(bg,s=F)  0.004 -0.260 -0.057                                   
scl(lg,s=F) -0.001 -0.318  0.057      -0.223                       
scl(sD,s=F)  0.006  0.134  0.035      -0.046     -0.280            
scl(tm,s=F)  0.000  0.230  0.111       0.095     -0.098       0.125
[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
 51676 51763 -25829    51658   51729
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0143788 0.119912
 sn       (Intercept) 0.0012299 0.035070
 Residual             0.0872112 0.295315
Number of obs: 126198, groups: id, 222; sn, 144

Fixed effects:
                                 Estimate Std. Error t value
(Intercept)                     5.2730138  0.0086061   612.7
scale(log_freq, scale = F)      0.0054301  0.0010474     5.2
scale(len, scale = F)          -0.0020047  0.0004428    -4.5
scale(bigram, scale = F)       -0.0139362  0.0003814   -36.5
scale(logitpred, scale = F)    -0.0107488  0.0010792   -10.0
scale(surprisalDep, scale = F)  0.0428869  0.0014470    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)  0.000                                          
scl(ln,s=F) -0.001  0.547                                   
scl(bg,s=F)  0.001 -0.314 -0.072                            
scl(lg,s=F)  0.000 -0.315  0.058      -0.216                
scl(sD,s=F)  0.005  0.118  0.012      -0.067     -0.287     
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
 52527 52614 -26254    52509   52590
Random effects:
 Groups   Name        Variance   Std.Dev.
 id       (Intercept) 0.01436605 0.119858
 sn       (Intercept) 0.00098768 0.031427
 Residual             0.08782303 0.296350
Number of obs: 126198, groups: id, 222; sn, 144

Fixed effects:
                              Estimate Std. Error t value
(Intercept)                  5.272e+00  8.505e-03   619.9
scale(log_freq, scale = F)   2.751e-03  1.063e-03     2.6
scale(len, scale = F)       -1.858e-03  4.467e-04    -4.2
scale(bigram, scale = F)    -1.301e-02  3.833e-04   -34.0
scale(logitpred, scale = F) -1.916e-03  1.038e-03    -1.8
scale(time, scale = F)       4.410e-05  9.443e-06     4.7

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  0.558                                   
scl(bg,s=F)  0.001 -0.281 -0.056                            
scl(lg,s=F)  0.001 -0.302  0.055      -0.251                
scl(tm,s=F) -0.001  0.197  0.128       0.107     -0.071     
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
 51610 51708 -25795    51590   51683
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0143718 0.119883
 sn       (Intercept) 0.0012106 0.034794
 Residual             0.0871660 0.295239
Number of obs: 126198, groups: id, 222; sn, 144

Fixed effects:
                                 Estimate Std. Error t value
(Intercept)                     5.273e+00  8.597e-03   613.4
scale(log_freq, scale = F)      7.280e-03  1.071e-03     6.8
scale(len, scale = F)          -1.523e-03  4.465e-04    -3.4
scale(bigram, scale = F)       -1.362e-02  3.831e-04   -35.6
scale(logitpred, scale = F)    -1.166e-02  1.085e-03   -10.7
scale(surprisalDep, scale = F)  4.428e-02  1.457e-03    30.4
scale(time, scale = F)          7.790e-05  9.486e-06     8.2

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  0.558                                          
scl(bg,s=F)  0.001 -0.284 -0.058                                   
scl(lg,s=F)  0.000 -0.328  0.044      -0.224                       
scl(sD,s=F)  0.005  0.139  0.028      -0.055     -0.295            
scl(tm,s=F) -0.001  0.211  0.131       0.100     -0.102       0.117
[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
 157260 157348 -78621   157242  157309
Random effects:
 Groups   Name        Variance Std.Dev.
 id       (Intercept) 0.031177 0.17657 
 sn       (Intercept) 0.005262 0.07254 
 Residual             0.185156 0.43030 
Number of obs: 135274, groups: id, 222; sn, 144

Fixed effects:
                                 Estimate Std. Error t value
(Intercept)                     5.4722298  0.0133586   409.6
scale(log_freq, scale = F)     -0.0043738  0.0014638    -3.0
scale(len, scale = F)           0.0359217  0.0006312    56.9
scale(bigram, scale = F)       -0.0082549  0.0005320   -15.5
scale(logitpred, scale = F)    -0.0136003  0.0015180    -9.0
scale(surprisalDep, scale = F)  0.0429916  0.0020420    21.1

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  0.564                                   
scl(bg,s=F)  0.001 -0.301 -0.076                            
scl(lg,s=F)  0.000 -0.321  0.057      -0.217                
scl(sD,s=F)  0.005  0.114  0.015      -0.058     -0.288     
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
 157686 157775 -78834   157668  157745
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0311565 0.176512
 sn       (Intercept) 0.0049833 0.070593
 Residual             0.1857527 0.430990
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)  -9.098e-03  1.488e-03    -6.1
scale(len, scale = F)        3.541e-02  6.368e-04    55.6
scale(bigram, scale = F)    -7.832e-03  5.346e-04   -14.7
scale(logitpred, scale = F) -4.026e-03  1.459e-03    -2.8
scale(time, scale = F)      -5.285e-05  1.331e-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  0.575                                   
scl(bg,s=F)  0.002 -0.269 -0.062                            
scl(lg,s=F)  0.001 -0.309  0.055      -0.249                
scl(tm,s=F) -0.001  0.205  0.124       0.102     -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
 157259 157358 -78620   157239  157327
Random effects:
 Groups   Name        Variance Std.Dev.
 id       (Intercept) 0.031177 0.176571
 sn       (Intercept) 0.005267 0.072574
 Residual             0.185152 0.430293
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)     -4.891e-03  1.499e-03    -3.3
scale(len, scale = F)           3.579e-02  6.363e-04    56.3
scale(bigram, scale = F)       -8.336e-03  5.344e-04   -15.6
scale(logitpred, scale = F)    -1.336e-02  1.525e-03    -8.8
scale(surprisalDep, scale = F)  4.262e-02  2.055e-03    20.7
scale(time, scale = F)         -2.131e-05  1.338e-05    -1.6

Correlation of Fixed Effects:
            (Intr) s(_s=F scl(ln,s=F) scl(b,s=F) scl(lg,s=F) s(Ds=F
scl(l_,s=F)  0.000                                                 
scl(ln,s=F) -0.001  0.574                                          
scl(bg,s=F)  0.001 -0.272 -0.063                                   
scl(lg,s=F)  0.000 -0.333  0.044      -0.224                       
scl(sD,s=F)  0.005  0.135  0.029      -0.046     -0.295            
scl(tm,s=F) -0.001  0.217  0.126       0.096     -0.097       0.114
[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
 140754 140842 -70368   140736  140803
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0294124 0.171500
 sn       (Intercept) 0.0052688 0.072586
 Residual             0.1638494 0.404783
Number of obs: 135274, groups: id, 222; sn, 144

Fixed effects:
                                 Estimate Std. Error t value
(Intercept)                     5.4541378  0.0130527   417.9
scale(log_freq, scale = F)      0.0021006  0.0013776     1.5
scale(len, scale = F)           0.0354585  0.0005942    59.7
scale(bigram, scale = F)       -0.0131772  0.0005007   -26.3
scale(logitpred, scale = F)    -0.0281786  0.0014286   -19.7
scale(surprisalDep, scale = F)  0.0369135  0.0019218    19.2

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  0.564                                   
scl(bg,s=F)  0.001 -0.301 -0.077                            
scl(lg,s=F)  0.000 -0.321  0.057      -0.217                
scl(sD,s=F)  0.004  0.114  0.015      -0.058     -0.288     
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
 141101 141189 -70541   141083  141160
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0293961 0.171453
 sn       (Intercept) 0.0050259 0.070893
 Residual             0.1642794 0.405314
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)  -2.242e-03  1.400e-03    -1.6
scale(len, scale = F)        3.495e-02  5.994e-04    58.3
scale(bigram, scale = F)    -1.287e-02  5.030e-04   -25.6
scale(logitpred, scale = F) -1.986e-02  1.373e-03   -14.5
scale(time, scale = F)      -5.788e-05  1.252e-05    -4.6

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  0.575                                   
scl(bg,s=F)  0.002 -0.268 -0.062                            
scl(lg,s=F)  0.001 -0.310  0.055      -0.250                
scl(tm,s=F) -0.001  0.205  0.124       0.102     -0.067     
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
 140750 140848 -70365   140730  140818
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0294121 0.171500
 sn       (Intercept) 0.0052759 0.072635
 Residual             0.1638418 0.404774
Number of obs: 135274, groups: id, 222; sn, 144

Fixed effects:
                                 Estimate Std. Error t value
(Intercept)                     5.454e+00  1.305e-02   417.8
scale(log_freq, scale = F)      1.347e-03  1.411e-03     1.0
scale(len, scale = F)           3.527e-02  5.990e-04    58.9
scale(bigram, scale = F)       -1.330e-02  5.030e-04   -26.4
scale(logitpred, scale = F)    -2.784e-02  1.435e-03   -19.4
scale(surprisalDep, scale = F)  3.637e-02  1.934e-03    18.8
scale(time, scale = F)         -3.102e-05  1.259e-05    -2.5

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  0.574                                          
scl(bg,s=F)  0.001 -0.272 -0.063                                   
scl(lg,s=F)  0.000 -0.333  0.044      -0.225                       
scl(sD,s=F)  0.004  0.135  0.029      -0.046     -0.296            
scl(tm,s=F) -0.001  0.217  0.126       0.096     -0.097       0.114
[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
 86390 86468 -43187    86374
Random effects:
 Groups Name        Variance Std.Dev.
 id     (Intercept) 0.70573  0.84008 
 sn     (Intercept) 0.10108  0.31793 
Number of obs: 135274, groups: id, 222; sn, 144

Fixed effects:
                                Estimate Std. Error z value Pr(>|z|)    
(Intercept)                    -2.362965   0.063343  -37.30  < 2e-16 ***
scale(log_freq, scale = F)     -0.157713   0.011086  -14.23  < 2e-16 ***
scale(len, scale = F)           0.013788   0.004574    3.01  0.00258 ** 
scale(bigram, scale = F)        0.079980   0.004105   19.48  < 2e-16 ***
scale(logitpred, scale = F)     0.015466   0.011551    1.34  0.18059    
scale(surprisalDep, scale = F)  0.166878   0.015321   10.89  < 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 -0.342 -0.071                            
scl(lg,s=F) -0.001 -0.301  0.067      -0.228                
scl(sD,s=F) -0.003  0.119 -0.003      -0.073     -0.289     
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
 88023 88101 -44003    88007
Random effects:
 Groups Name        Variance Std.Dev.
 id     (Intercept) 0.053196 0.23064 
 sn     (Intercept) 0.010536 0.10264 
Number of obs: 135274, groups: id, 222; sn, 144

Fixed effects:
                              Estimate Std. Error z value Pr(>|z|)    
(Intercept)                 -2.100e+00  2.013e-02 -104.37  < 2e-16 ***
scale(log_freq, scale = F)  -1.646e-01  1.063e-02  -15.48  < 2e-16 ***
scale(len, scale = F)        2.496e-03  4.307e-03    0.58  0.56220    
scale(bigram, scale = F)     6.968e-02  3.849e-03   18.11  < 2e-16 ***
scale(logitpred, scale = F)  3.367e-02  1.045e-02    3.22  0.00126 ** 
scale(time, scale = F)      -1.438e-04  9.576e-05   -1.50  0.13320    
---
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)  0.045                                          
scl(ln,s=F) -0.002  0.531                                   
scl(bg,s=F) -0.049 -0.331 -0.040                            
scl(lg,s=F) -0.005 -0.278  0.075      -0.248                
scl(tm,s=F)  0.002  0.202  0.130       0.088     -0.073     
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
 87369 87457 -43675    87351
Random effects:
 Groups Name        Variance Std.Dev.
 id     (Intercept) 0.079893 0.28265 
 sn     (Intercept) 0.019346 0.13909 
Number of obs: 135274, groups: id, 222; sn, 144

Fixed effects:
                                 Estimate Std. Error z value Pr(>|z|)    
(Intercept)                    -2.119e+00  2.434e-02  -87.03   <2e-16 ***
scale(log_freq, scale = F)     -1.530e-01  1.092e-02  -14.01   <2e-16 ***
scale(len, scale = F)           6.653e-03  4.402e-03    1.51    0.131    
scale(bigram, scale = F)        7.041e-02  3.930e-03   17.92   <2e-16 ***
scale(logitpred, scale = F)     1.206e-02  1.107e-02    1.09    0.276    
scale(surprisalDep, scale = F)  1.377e-01  1.468e-02    9.38   <2e-16 ***
scale(time, scale = F)         -6.562e-05  9.832e-05   -0.67    0.504    
---
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)  0.036                                                 
scl(ln,s=F) -0.003  0.538                                          
scl(bg,s=F) -0.040 -0.331 -0.049                                   
scl(lg,s=F) -0.002 -0.305  0.059      -0.218                       
scl(sD,s=F) -0.008  0.140  0.026      -0.081     -0.283            
scl(tm,s=F)  0.001  0.223  0.135       0.073     -0.097       0.121
