[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) 0.0150459 0.122662
 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  0.0088087   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
 42775 42861 -21379    42757   42827
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0150523 0.12269 
 sn       (Intercept) 0.0014183 0.03766 
 Residual             0.0883004 0.29715 
Number of obs: 100860, groups: id, 222; sn, 144

Fixed effects:
                                 Estimate Std. Error t value
(Intercept)                     5.2762698  0.0088679   595.0
scale(log_freq, scale = F)      0.0005772  0.0011647     0.5
scale(len, scale = F)           0.0058330  0.0005685    10.3
scale(bigram, scale = F)       -0.0131608  0.0004117   -32.0
scale(logitpred, scale = F)    -0.0133459  0.0011737   -11.4
scale(surprisalDep, scale = F)  0.0425192  0.0019991    21.3

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  0.562                                   
scl(bg,s=F)  0.004 -0.291 -0.067                            
scl(lg,s=F) -0.001 -0.309  0.072      -0.215                
scl(sD,s=F)  0.007  0.124  0.008      -0.057     -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
 42926 43012 -21454    42908   42988
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0150139 0.122531
 sn       (Intercept) 0.0013355 0.036545
 Residual             0.0884403 0.297389
Number of obs: 100860, groups: id, 222; sn, 144

Fixed effects:
                              Estimate Std. Error t value
(Intercept)                  5.275e+00  8.826e-03   597.7
scale(log_freq, scale = F)  -2.186e-03  1.156e-03    -1.9
scale(len, scale = F)        6.439e-03  5.699e-04    11.3
scale(bigram, scale = F)    -1.121e-02  4.197e-04   -26.7
scale(logitpred, scale = F) -9.729e-03  1.144e-03    -8.5
scale(time, scale = F)       1.476e-04  8.515e-06    17.3

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  0.565                                   
scl(bg,s=F)  0.004 -0.278 -0.051                            
scl(lg,s=F)  0.001 -0.286  0.064      -0.266                
scl(tm,s=F) -0.001  0.015  0.070       0.201     -0.170     
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
 42448 42543 -21214    42428   42519
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0150195 0.122554
 sn       (Intercept) 0.0014515 0.038099
 Residual             0.0880092 0.296663
Number of obs: 100860, groups: id, 222; sn, 144

Fixed effects:
                                 Estimate Std. Error t value
(Intercept)                     5.276e+00  8.872e-03   594.7
scale(log_freq, scale = F)      9.824e-04  1.163e-03     0.8
scale(len, scale = F)           6.555e-03  5.691e-04    11.5
scale(bigram, scale = F)       -1.164e-02  4.194e-04   -27.8
scale(logitpred, scale = F)    -1.709e-02  1.190e-03   -14.4
scale(surprisalDep, scale = F)  4.384e-02  1.998e-03    21.9
scale(time, scale = F)          1.545e-04  8.504e-06    18.2

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) -0.002  0.562                                          
scl(bg,s=F)  0.004 -0.282 -0.052                                   
scl(lg,s=F) -0.001 -0.308  0.059      -0.242                       
scl(sD,s=F)  0.007  0.124  0.010      -0.048     -0.281            
scl(tm,s=F) -0.001  0.019  0.070       0.199     -0.173       0.036
[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) 0.01437030 0.119876
 sn       (Intercept) 0.00099265 0.031506
 Residual             0.08783775 0.296374
Number of obs: 126198, groups: id, 222; sn, 144

Fixed effects:
                              Estimate Std. Error t value
(Intercept)                  5.2717863  0.0085078   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
 51736 51823 -25859    51718   51788
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0143827 0.119928
 sn       (Intercept) 0.0012058 0.034724
 Residual             0.0872545 0.295389
Number of obs: 126198, groups: id, 222; sn, 144

Fixed effects:
                                 Estimate Std. Error t value
(Intercept)                     5.2731925  0.0085976   613.3
scale(log_freq, scale = F)      0.0059062  0.0010503     5.6
scale(len, scale = F)          -0.0021452  0.0004428    -4.8
scale(bigram, scale = F)       -0.0138934  0.0003814   -36.4
scale(logitpred, scale = F)    -0.0106527  0.0010816    -9.8
scale(surprisalDep, scale = F)  0.0513581  0.0017961    28.6

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  0.544                                   
scl(bg,s=F)  0.001 -0.314 -0.071                            
scl(lg,s=F) -0.001 -0.320  0.061      -0.216                
scl(sD,s=F)  0.006  0.138  0.002      -0.065     -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
 52129 52216 -26055    52111   52192
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0143589 0.119829
 sn       (Intercept) 0.0010514 0.032425
 Residual             0.0875402 0.295872
Number of obs: 126198, groups: id, 222; sn, 144

Fixed effects:
                              Estimate Std. Error t value
(Intercept)                  5.272e+00  8.529e-03   618.1
scale(log_freq, scale = F)   1.793e-03  1.041e-03     1.7
scale(len, scale = F)       -1.401e-03  4.442e-04    -3.2
scale(bigram, scale = F)    -1.158e-02  3.888e-04   -29.8
scale(logitpred, scale = F) -5.427e-03  1.052e-03    -5.2
scale(time, scale = F)       1.550e-04  7.556e-06    20.5

Correlation of Fixed Effects:
            (Intr) s(_s=F scl(ln,s=F) scl(b,s=F) scl(lg,s=F)
scl(l_,s=F)  0.000                                          
scl(ln,s=F) -0.001  0.547                                   
scl(bg,s=F)  0.001 -0.303 -0.053                            
scl(lg,s=F)  0.001 -0.290  0.049      -0.273                
scl(tm,s=F) -0.001  0.001  0.081       0.202     -0.179     
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
 51291 51389 -25636    51271   51364
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0143714 0.119881
 sn       (Intercept) 0.0012223 0.034961
 Residual             0.0869445 0.294864
Number of obs: 126198, groups: id, 222; sn, 144

Fixed effects:
                                 Estimate Std. Error t value
(Intercept)                     5.273e+00  8.601e-03   613.1
scale(log_freq, scale = F)      5.982e-03  1.049e-03     5.7
scale(len, scale = F)          -1.390e-03  4.436e-04    -3.1
scale(bigram, scale = F)       -1.224e-02  3.887e-04   -31.5
scale(logitpred, scale = F)    -1.475e-02  1.097e-03   -13.4
scale(surprisalDep, scale = F)  5.209e-02  1.793e-03    29.0
scale(time, scale = F)          1.594e-04  7.538e-06    21.1

Correlation of Fixed Effects:
            (Intr) s(_s=F scl(ln,s=F) scl(b,s=F) scl(lg,s=F) s(Ds=F
scl(l_,s=F)  0.001                                                 
scl(ln,s=F) -0.001  0.543                                          
scl(bg,s=F)  0.001 -0.307 -0.054                                   
scl(lg,s=F) -0.001 -0.316  0.046      -0.244                       
scl(sD,s=F)  0.006  0.138  0.003      -0.060     -0.292            
scl(tm,s=F) -0.001  0.003  0.081       0.201     -0.176       0.019
[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) 0.0311557 0.176510
 sn       (Intercept) 0.0049761 0.070541
 Residual             0.1857746 0.431016
Number of obs: 135274, groups: id, 222; sn, 144

Fixed effects:
                              Estimate Std. Error t value
(Intercept)                  5.4709308  0.0132803   412.0
scale(log_freq, scale = F)  -0.0078903  0.0014564    -5.4
scale(len, scale = F)        0.0357235  0.0006320    56.5
scale(bigram, scale = F)    -0.0076166  0.0005318   -14.3
scale(logitpred, scale = F) -0.0044125  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
 157235 157324 -78609   157217  157284
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0311802 0.17658 
 sn       (Intercept) 0.0052621 0.07254 
 Residual             0.1851220 0.43026 
Number of obs: 135274, groups: id, 222; sn, 144

Fixed effects:
                                 Estimate Std. Error t value
(Intercept)                     5.4725151  0.0133591   409.6
scale(log_freq, scale = F)     -0.0037200  0.0014668    -2.5
scale(len, scale = F)           0.0357687  0.0006311    56.7
scale(bigram, scale = F)       -0.0082422  0.0005319   -15.5
scale(logitpred, scale = F)    -0.0140624  0.0015207    -9.2
scale(surprisalDep, scale = F)  0.0548359  0.0025348    21.6

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  0.562                                   
scl(bg,s=F)  0.001 -0.301 -0.076                            
scl(lg,s=F) -0.001 -0.325  0.060      -0.217                
scl(sD,s=F)  0.005  0.131  0.003      -0.055     -0.293     
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
 157623 157711 -78803   157605  157682
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0311568 0.176513
 sn       (Intercept) 0.0049611 0.070435
 Residual             0.1856662 0.430890
Number of obs: 135274, groups: id, 222; sn, 144

Fixed effects:
                              Estimate Std. Error t value
(Intercept)                  5.471e+00  1.328e-02   412.1
scale(log_freq, scale = F)  -7.807e-03  1.456e-03    -5.4
scale(len, scale = F)        3.617e-02  6.338e-04    57.1
scale(bigram, scale = F)    -6.650e-03  5.427e-04   -12.3
scale(logitpred, scale = F) -6.739e-03  1.479e-03    -4.6
scale(time, scale = F)       9.445e-05  1.062e-05     8.9

Correlation of Fixed Effects:
            (Intr) s(_s=F scl(ln,s=F) scl(b,s=F) scl(lg,s=F)
scl(l_,s=F) -0.001                                          
scl(ln,s=F) -0.001  0.565                                   
scl(bg,s=F)  0.002 -0.290 -0.058                            
scl(lg,s=F)  0.001 -0.299  0.048      -0.271                
scl(tm,s=F) -0.001  0.006  0.080       0.200     -0.177     
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
 157150 157248 -78565   157130  157217
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0311805 0.176580
 sn       (Intercept) 0.0052181 0.072237
 Residual             0.1850039 0.430121
Number of obs: 135274, groups: id, 222; sn, 144

Fixed effects:
                                 Estimate Std. Error t value
(Intercept)                     5.472e+00  1.335e-02   410.0
scale(log_freq, scale = F)     -3.599e-03  1.466e-03    -2.5
scale(len, scale = F)           3.624e-02  6.328e-04    57.3
scale(bigram, scale = F)       -7.235e-03  5.425e-04   -13.3
scale(logitpred, scale = F)    -1.658e-02  1.544e-03   -10.7
scale(surprisalDep, scale = F)  5.530e-02  2.534e-03    21.8
scale(time, scale = F)          9.903e-05  1.060e-05     9.3

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  0.560                                          
scl(bg,s=F)  0.001 -0.294 -0.058                                   
scl(lg,s=F) -0.001 -0.322  0.045      -0.244                       
scl(sD,s=F)  0.005  0.131  0.005      -0.050     -0.292            
scl(tm,s=F) -0.001  0.009  0.080       0.199     -0.175       0.020
[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  0.0129836   420.0
scale(log_freq, scale = F)  -0.0009175  0.0013703    -0.7
scale(len, scale = F)        0.0352919  0.0005948    59.3
scale(bigram, scale = F)    -0.0126309  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
 140759 140847 -70370   140741  140808
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0294143 0.17151 
 sn       (Intercept) 0.0052563 0.07250 
 Residual             0.1638560 0.40479 
Number of obs: 135274, groups: id, 222; sn, 144

Fixed effects:
                                 Estimate Std. Error t value
(Intercept)                     5.4543380  0.0130508   417.9
scale(log_freq, scale = F)      0.0025427  0.0013806     1.8
scale(len, scale = F)           0.0353259  0.0005941    59.5
scale(bigram, scale = F)       -0.0131481  0.0005006   -26.3
scale(logitpred, scale = F)    -0.0282986  0.0014313   -19.8
scale(surprisalDep, scale = F)  0.0455089  0.0023858    19.1

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  0.562                                   
scl(bg,s=F)  0.001 -0.301 -0.076                            
scl(lg,s=F) -0.001 -0.326  0.060      -0.217                
scl(sD,s=F)  0.005  0.131  0.003      -0.055     -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
 141064 141152 -70523   141046  141124
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0293978 0.171458
 sn       (Intercept) 0.0049995 0.070707
 Residual             0.1642352 0.405259
Number of obs: 135274, groups: id, 222; sn, 144

Fixed effects:
                              Estimate Std. Error t value
(Intercept)                  5.453e+00  1.298e-02   420.2
scale(log_freq, scale = F)  -8.505e-04  1.370e-03    -0.6
scale(len, scale = F)        3.565e-02  5.965e-04    59.8
scale(bigram, scale = F)    -1.185e-02  5.107e-04   -23.2
scale(logitpred, scale = F) -2.216e-02  1.391e-03   -15.9
scale(time, scale = F)       7.633e-05  9.987e-06     7.6

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  0.565                                   
scl(bg,s=F)  0.002 -0.290 -0.058                            
scl(lg,s=F)  0.001 -0.299  0.048      -0.271                
scl(tm,s=F) -0.001  0.006  0.080       0.200     -0.177     
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
 140696 140795 -70338   140676  140765
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0294164 0.171512
 sn       (Intercept) 0.0052198 0.072248
 Residual             0.1637789 0.404696
Number of obs: 135274, groups: id, 222; sn, 144

Fixed effects:
                                 Estimate Std. Error t value
(Intercept)                     5.454e+00  1.304e-02   418.3
scale(log_freq, scale = F)      2.640e-03  1.380e-03     1.9
scale(len, scale = F)           3.571e-02  5.958e-04    59.9
scale(bigram, scale = F)       -1.233e-02  5.107e-04   -24.2
scale(logitpred, scale = F)    -3.034e-02  1.453e-03   -20.9
scale(surprisalDep, scale = F)  4.588e-02  2.386e-03    19.2
scale(time, scale = F)          8.008e-05  9.976e-06     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)  0.000                                                 
scl(ln,s=F) -0.001  0.561                                          
scl(bg,s=F)  0.001 -0.293 -0.058                                   
scl(lg,s=F) -0.001 -0.322  0.045      -0.245                       
scl(sD,s=F)  0.005  0.131  0.004      -0.050     -0.292            
scl(tm,s=F) -0.001  0.009  0.080       0.199     -0.175       0.020
[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) 0.704276 0.83921 
 sn     (Intercept) 0.099178 0.31492 
Number of obs: 135274, groups: id, 222; sn, 144

Fixed effects:
                             Estimate Std. Error z value Pr(>|z|)    
(Intercept)                 -2.364249   0.063185  -37.42  < 2e-16 ***
scale(log_freq, scale = F)  -0.172154   0.011039  -15.60  < 2e-16 ***
scale(len, scale = F)        0.013886   0.004571    3.04  0.00239 ** 
scale(bigram, scale = F)     0.083165   0.004105   20.26  < 2e-16 ***
scale(logitpred, scale = F)  0.051934   0.011063    4.69 2.68e-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
 86393 86472 -43189    86377
Random effects:
 Groups Name        Variance Std.Dev.
 id     (Intercept) 0.70571  0.84006 
 sn     (Intercept) 0.10035  0.31677 
Number of obs: 135274, groups: id, 222; sn, 144

Fixed effects:
                                Estimate Std. Error z value Pr(>|z|)    
(Intercept)                    -2.361984   0.063302  -37.31  < 2e-16 ***
scale(log_freq, scale = F)     -0.156272   0.011110  -14.07  < 2e-16 ***
scale(len, scale = F)           0.013166   0.004576    2.88  0.00402 ** 
scale(bigram, scale = F)        0.080258   0.004104   19.55  < 2e-16 ***
scale(logitpred, scale = F)     0.015062   0.011576    1.30  0.19321    
scale(surprisalDep, scale = F)  0.203161   0.018896   10.75  < 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) -0.018 -0.342 -0.071                            
scl(lg,s=F) -0.002 -0.304  0.070      -0.229                
scl(sD,s=F) -0.001  0.133 -0.014      -0.066     -0.299     
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
 86500 86578 -43242    86484
Random effects:
 Groups Name        Variance Std.Dev.
 id     (Intercept) 0.704332 0.83925 
 sn     (Intercept) 0.098335 0.31358 
Number of obs: 135274, groups: id, 222; sn, 144

Fixed effects:
                              Estimate Std. Error z value Pr(>|z|)    
(Intercept)                 -2.365e+00  6.314e-02  -37.45  < 2e-16 ***
scale(log_freq, scale = F)  -1.714e-01  1.104e-02  -15.53  < 2e-16 ***
scale(len, scale = F)        1.496e-02  4.588e-03    3.26  0.00111 ** 
scale(bigram, scale = F)     8.526e-02  4.178e-03   20.41  < 2e-16 ***
scale(logitpred, scale = F)  4.649e-02  1.124e-02    4.14 3.55e-05 ***
scale(time, scale = F)       2.165e-04  7.972e-05    2.72  0.00661 ** 
---
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  0.539                                   
scl(bg,s=F) -0.018 -0.327 -0.053                            
scl(lg,s=F) -0.002 -0.282  0.052      -0.288                
scl(tm,s=F) -0.003  0.024  0.087       0.187     -0.178     
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
 86387 86475 -43184    86369
Random effects:
 Groups Name        Variance Std.Dev.
 id     (Intercept) 0.705795 0.84012 
 sn     (Intercept) 0.099094 0.31479 
Number of obs: 135274, groups: id, 222; sn, 144

Fixed effects:
                                 Estimate Std. Error z value Pr(>|z|)    
(Intercept)                    -2.362e+00  6.324e-02  -37.36  < 2e-16 ***
scale(log_freq, scale = F)     -1.554e-01  1.111e-02  -13.98  < 2e-16 ***
scale(len, scale = F)           1.431e-02  4.592e-03    3.12  0.00184 ** 
scale(bigram, scale = F)        8.240e-02  4.172e-03   19.75  < 2e-16 ***
scale(logitpred, scale = F)     9.283e-03  1.174e-02    0.79  0.42895    
scale(surprisalDep, scale = F)  2.045e-01  1.893e-02   10.80  < 2e-16 ***
scale(time, scale = F)          2.327e-04  8.023e-05    2.90  0.00372 ** 
---
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)  0.015                                                 
scl(ln,s=F) -0.004  0.535                                          
scl(bg,s=F) -0.018 -0.332 -0.053                                   
scl(lg,s=F) -0.001 -0.303  0.053      -0.252                       
scl(sD,s=F) -0.001  0.135 -0.012      -0.062     -0.297            
scl(tm,s=F) -0.004  0.028  0.087       0.179     -0.169       0.025
[1] 0.7142857
[1] 100
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) 0.0150459 0.122662
 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  0.0088087   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    
