[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
 42802 42888 -21392    42784   42854
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0150643 0.122737
 sn       (Intercept) 0.0013953 0.037354
 Residual             0.0883700 0.297271
Number of obs: 100739, groups: id, 222; sn, 144

Fixed effects:
                                 Estimate Std. Error t value
(Intercept)                     5.2757490  0.0088620   595.3
scale(log_freq, scale = F)     -0.0008159  0.0011594    -0.7
scale(len, scale = F)           0.0058734  0.0005686    10.3
scale(bigram, scale = F)       -0.0128904  0.0004116   -31.3
scale(logitpred, scale = F)    -0.0121177  0.0011659   -10.4
scale(surprisalDep, scale = F)  0.0287995  0.0014983    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) -0.001                                          
scl(ln,s=F) -0.002  0.564                                   
scl(bg,s=F)  0.004 -0.288 -0.067                            
scl(lg,s=F)  0.000 -0.297  0.072      -0.226                
scl(sD,s=F)  0.005  0.073  0.012      -0.025     -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
 43170 43256 -21576    43152   43232
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0150679 0.122751
 sn       (Intercept) 0.0012603 0.035501
 Residual             0.0887061 0.297836
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)  -2.554e-03  1.190e-03    -2.1
scale(len, scale = F)        5.761e-03  5.689e-04    10.1
scale(bigram, scale = F)    -1.270e-02  4.120e-04   -30.8
scale(logitpred, scale = F) -6.328e-03  1.139e-03    -5.6
scale(time, scale = F)      -5.218e-06  1.335e-05    -0.4

Correlation of Fixed Effects:
            (Intr) s(_s=F scl(ln,s=F) scl(b,s=F) scl(lg,s=F)
scl(l_,s=F) -0.001                                          
scl(ln,s=F) -0.002  0.547                                   
scl(bg,s=F)  0.004 -0.286 -0.066                            
scl(lg,s=F)  0.001 -0.309  0.078      -0.234                
scl(tm,s=F)  0.001  0.231 -0.010      -0.024     -0.135     
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
 42804 42899 -21392    42784   42874
Random effects:
 Groups   Name        Variance Std.Dev.
 id       (Intercept) 0.015066 0.12274 
 sn       (Intercept) 0.001395 0.03735 
 Residual             0.088370 0.29727 
Number of obs: 100739, groups: id, 222; sn, 144

Fixed effects:
                                 Estimate Std. Error t value
(Intercept)                     5.276e+00  8.862e-03   595.3
scale(log_freq, scale = F)     -1.006e-03  1.191e-03    -0.8
scale(len, scale = F)           5.877e-03  5.686e-04    10.3
scale(bigram, scale = F)       -1.288e-02  4.117e-04   -31.3
scale(logitpred, scale = F)    -1.201e-02  1.175e-03   -10.2
scale(surprisalDep, scale = F)  2.882e-02  1.499e-03    19.2
scale(time, scale = F)         -9.279e-06  1.333e-05    -0.7

Correlation of Fixed Effects:
            (Intr) s(_s=F scl(ln,s=F) scl(b,s=F) scl(lg,s=F) s(Ds=F
scl(l_,s=F) -0.001                                                 
scl(ln,s=F) -0.002  0.547                                          
scl(bg,s=F)  0.004 -0.286 -0.067                                   
scl(lg,s=F)  0.000 -0.316  0.072      -0.221                       
scl(sD,s=F)  0.005  0.068  0.012      -0.024     -0.251            
scl(tm,s=F)  0.001  0.229 -0.010      -0.023     -0.126      -0.016
[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
 51705 51793 -25843    51687   51758
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0143859 0.119941
 sn       (Intercept) 0.0012026 0.034678
 Residual             0.0872837 0.295438
Number of obs: 126018, groups: id, 222; sn, 144

Fixed effects:
                                 Estimate Std. Error t value
(Intercept)                     5.2727199  0.0085970   613.3
scale(log_freq, scale = F)      0.0042391  0.0010443     4.1
scale(len, scale = F)          -0.0021011  0.0004429    -4.7
scale(bigram, scale = F)       -0.0134955  0.0003811   -35.4
scale(logitpred, scale = F)    -0.0097535  0.0010755    -9.1
scale(surprisalDep, scale = F)  0.0370523  0.0013402    27.6

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  0.548                                   
scl(bg,s=F)  0.001 -0.310 -0.072                            
scl(lg,s=F)  0.000 -0.306  0.061      -0.229                
scl(sD,s=F)  0.004  0.085  0.004      -0.027     -0.274     
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
 52465 52552 -26223    52447   52527
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0143810 0.119921
 sn       (Intercept) 0.0009839 0.031367
 Residual             0.0878312 0.296363
Number of obs: 126018, groups: id, 222; sn, 144

Fixed effects:
                              Estimate Std. Error t value
(Intercept)                  5.272e+00  8.507e-03   619.7
scale(log_freq, scale = F)   1.852e-03  1.068e-03     1.7
scale(len, scale = F)       -2.117e-03  4.431e-04    -4.8
scale(bigram, scale = F)    -1.324e-02  3.816e-04   -34.7
scale(logitpred, scale = F) -1.638e-03  1.046e-03    -1.6
scale(time, scale = F)       2.759e-06  1.179e-05     0.2

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  0.533                                   
scl(bg,s=F)  0.001 -0.308 -0.070                            
scl(lg,s=F)  0.001 -0.315  0.066      -0.238                
scl(tm,s=F)  0.001  0.219 -0.011      -0.029     -0.138     
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
 51707 51804 -25843    51687   51779
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0143867 0.119945
 sn       (Intercept) 0.0012024 0.034675
 Residual             0.0872836 0.295438
Number of obs: 126018, groups: id, 222; sn, 144

Fixed effects:
                                 Estimate Std. Error t value
(Intercept)                     5.273e+00  8.597e-03   613.3
scale(log_freq, scale = F)      4.140e-03  1.070e-03     3.9
scale(len, scale = F)          -2.099e-03  4.429e-04    -4.7
scale(bigram, scale = F)       -1.349e-02  3.812e-04   -35.4
scale(logitpred, scale = F)    -9.695e-03  1.084e-03    -8.9
scale(surprisalDep, scale = F)  3.707e-02  1.341e-03    27.6
scale(time, scale = F)         -5.040e-06  1.178e-05    -0.4

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  0.532                                          
scl(bg,s=F)  0.001 -0.309 -0.072                                   
scl(lg,s=F)  0.000 -0.324  0.062      -0.223                       
scl(sD,s=F)  0.004  0.077  0.005      -0.027     -0.269            
scl(tm,s=F)  0.000  0.217 -0.011      -0.028     -0.127      -0.024
[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
 157205 157293 -78593   157187  157254
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0311890 0.176604
 sn       (Intercept) 0.0052075 0.072163
 Residual             0.1853691 0.430545
Number of obs: 135093, groups: id, 222; sn, 144

Fixed effects:
                                 Estimate Std. Error t value
(Intercept)                     5.4717406  0.0133463   410.0
scale(log_freq, scale = F)     -0.0059027  0.0014600    -4.0
scale(len, scale = F)           0.0357998  0.0006315    56.7
scale(bigram, scale = F)       -0.0078259  0.0005320   -14.7
scale(logitpred, scale = F)    -0.0113392  0.0015118    -7.5
scale(surprisalDep, scale = F)  0.0317365  0.0018879    16.8

Correlation of Fixed Effects:
            (Intr) s(_s=F scl(ln,s=F) scl(b,s=F) scl(lg,s=F)
scl(l_,s=F)  0.000                                          
scl(ln,s=F) -0.001  0.565                                   
scl(bg,s=F)  0.002 -0.298 -0.076                            
scl(lg,s=F)  0.000 -0.312  0.059      -0.228                
scl(sD,s=F)  0.004  0.080  0.006      -0.023     -0.272     
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
 157459 157547 -78721   157441  157518
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0311841 0.176590
 sn       (Intercept) 0.0049438 0.070312
 Residual             0.1857294 0.430963
Number of obs: 135093, 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)  -9.621e-03  1.494e-03    -6.4
scale(len, scale = F)        3.576e-02  6.319e-04    56.6
scale(bigram, scale = F)    -7.558e-03  5.324e-04   -14.2
scale(logitpred, scale = F) -3.395e-03  1.469e-03    -2.3
scale(time, scale = F)      -8.783e-05  1.668e-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)  0.000                                          
scl(ln,s=F) -0.001  0.549                                   
scl(bg,s=F)  0.002 -0.296 -0.075                            
scl(lg,s=F)  0.001 -0.323  0.064      -0.237                
scl(tm,s=F)  0.001  0.222 -0.010      -0.027     -0.134     
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
 157174 157272 -78577   157154  157241
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0311966 0.176626
 sn       (Intercept) 0.0051888 0.072033
 Residual             0.1853244 0.430493
Number of obs: 135093, groups: id, 222; sn, 144

Fixed effects:
                                 Estimate Std. Error t value
(Intercept)                     5.472e+00  1.334e-02   410.1
scale(log_freq, scale = F)     -7.786e-03  1.496e-03    -5.2
scale(len, scale = F)           3.584e-02  6.314e-04    56.8
scale(bigram, scale = F)       -7.746e-03  5.321e-04   -14.6
scale(logitpred, scale = F)    -1.027e-02  1.523e-03    -6.7
scale(surprisalDep, scale = F)  3.203e-02  1.888e-03    17.0
scale(time, scale = F)         -9.561e-05  1.667e-05    -5.7

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  0.549                                          
scl(bg,s=F)  0.002 -0.297 -0.076                                   
scl(lg,s=F)  0.000 -0.329  0.060      -0.223                       
scl(sD,s=F)  0.004  0.072  0.007      -0.022     -0.266            
scl(tm,s=F)  0.001  0.219 -0.011      -0.026     -0.122      -0.028
[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
 140682 140770 -70332   140664  140731
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0294204 0.171524
 sn       (Intercept) 0.0052628 0.072545
 Residual             0.1639891 0.404956
Number of obs: 135093, groups: id, 222; sn, 144

Fixed effects:
                                 Estimate Std. Error t value
(Intercept)                     5.4538261  0.0130527   417.8
scale(log_freq, scale = F)      0.0007742  0.0013738     0.6
scale(len, scale = F)           0.0353476  0.0005944    59.5
scale(bigram, scale = F)       -0.0127690  0.0005006   -25.5
scale(logitpred, scale = F)    -0.0263227  0.0014227   -18.5
scale(surprisalDep, scale = F)  0.0278686  0.0017764    15.7

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  0.565                                   
scl(bg,s=F)  0.002 -0.298 -0.076                            
scl(lg,s=F)  0.000 -0.313  0.059      -0.228                
scl(sD,s=F)  0.004  0.080  0.006      -0.022     -0.272     
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
 140884 140972 -70433   140866  140943
Random effects:
 Groups   Name        Variance Std.Dev.
 id       (Intercept) 0.029419 0.171519
 sn       (Intercept) 0.004998 0.070696
 Residual             0.164244 0.405270
Number of obs: 135093, 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)  -3.023e-03  1.405e-03    -2.2
scale(len, scale = F)        3.533e-02  5.947e-04    59.4
scale(bigram, scale = F)    -1.251e-02  5.010e-04   -25.0
scale(logitpred, scale = F) -1.903e-02  1.382e-03   -13.8
scale(time, scale = F)      -1.039e-04  1.569e-05    -6.6

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)  0.002 -0.296 -0.076                            
scl(lg,s=F)  0.001 -0.323  0.064      -0.238                
scl(tm,s=F)  0.001  0.222 -0.010      -0.027     -0.134     
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
 140634 140732 -70307   140614  140702
Random effects:
 Groups   Name        Variance  Std.Dev.
 id       (Intercept) 0.0294284 0.171547
 sn       (Intercept) 0.0052284 0.072308
 Residual             0.1639295 0.404882
Number of obs: 135093, 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)     -1.408e-03  1.408e-03    -1.0
scale(len, scale = F)           3.539e-02  5.943e-04    59.6
scale(bigram, scale = F)       -1.268e-02  5.007e-04   -25.3
scale(logitpred, scale = F)    -2.509e-02  1.433e-03   -17.5
scale(surprisalDep, scale = F)  2.821e-02  1.777e-03    15.9
scale(time, scale = F)         -1.107e-04  1.568e-05    -7.1

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  0.549                                          
scl(bg,s=F)  0.002 -0.297 -0.076                                   
scl(lg,s=F)  0.000 -0.329  0.060      -0.223                       
scl(sD,s=F)  0.004  0.072  0.007      -0.022     -0.267            
scl(tm,s=F)  0.001  0.219 -0.011      -0.026     -0.122      -0.028
[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
 86274 86353 -43129    86258
Random effects:
 Groups Name        Variance Std.Dev.
 id     (Intercept) 0.70475  0.83949 
 sn     (Intercept) 0.10063  0.31722 
Number of obs: 135093, groups: id, 222; sn, 144

Fixed effects:
                                Estimate Std. Error z value Pr(>|z|)    
(Intercept)                    -2.363763   0.063284  -37.35  < 2e-16 ***
scale(log_freq, scale = F)     -0.164184   0.011051  -14.86  < 2e-16 ***
scale(len, scale = F)           0.013526   0.004574    2.96  0.00311 ** 
scale(bigram, scale = F)        0.081912   0.004107   19.94  < 2e-16 ***
scale(logitpred, scale = F)     0.025074   0.011524    2.18  0.02957 *  
scale(surprisalDep, scale = F)  0.118490   0.014470    8.19 2.64e-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) -0.002 -0.292  0.069      -0.243                
scl(sD,s=F) -0.002  0.081 -0.012      -0.030     -0.280     
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
 86426 86505 -43205    86410
Random effects:
 Groups Name        Variance Std.Dev.
 id     (Intercept) 0.32297  0.56831 
 sn     (Intercept) 0.06374  0.25247 
Number of obs: 135093, groups: id, 222; sn, 144

Fixed effects:
                              Estimate Std. Error z value Pr(>|z|)    
(Intercept)                 -2.298e+00  4.492e-02  -51.16  < 2e-16 ***
scale(log_freq, scale = F)  -1.733e-01  1.126e-02  -15.40  < 2e-16 ***
scale(len, scale = F)        7.064e-03  4.547e-03    1.55    0.120    
scale(bigram, scale = F)     7.971e-02  4.068e-03   19.59  < 2e-16 ***
scale(logitpred, scale = F)  5.828e-02  1.107e-02    5.27 1.40e-07 ***
scale(time, scale = F)      -6.669e-05  1.245e-04   -0.54    0.592    
---
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  0.521                                   
scl(bg,s=F) -0.024 -0.337 -0.069                            
scl(lg,s=F) -0.005 -0.305  0.071      -0.251                
scl(tm,s=F)  0.002  0.234 -0.006      -0.036     -0.138     
Generalized linear mixed model fit by the Laplace approximation 
Formula: reg ~ scale(log_freq, scale = F) + scale(len, scale = F) + scale(bigram,      scale = F) + scale(logitpred, scale = F) + scale(surprisalDep,      scale = F) + scale(time, scale = F) + (1 | sn) + (1 | id) 
   Data: d.reg 
   AIC   BIC logLik deviance
 87046 87134 -43514    87028
Random effects:
 Groups Name        Variance Std.Dev.
 id     (Intercept) 0.093167 0.30523 
 sn     (Intercept) 0.028501 0.16882 
Number of obs: 135093, groups: id, 222; sn, 144

Fixed effects:
                                 Estimate Std. Error z value Pr(>|z|)    
(Intercept)                    -2.1257868  0.0268133  -79.28  < 2e-16 ***
scale(log_freq, scale = F)     -0.1597273  0.0110161  -14.50  < 2e-16 ***
scale(len, scale = F)           0.0097811  0.0044108    2.22   0.0266 *  
scale(bigram, scale = F)        0.0751523  0.0039656   18.95  < 2e-16 ***
scale(logitpred, scale = F)     0.0211091  0.0112145    1.88   0.0598 .  
scale(surprisalDep, scale = F)  0.1000000  0.0139760    7.16 8.36e-13 ***
scale(time, scale = F)         -0.0001313  0.0001222   -1.07   0.2827    
---
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)  0.034                                                 
scl(ln,s=F) -0.005  0.515                                          
scl(bg,s=F) -0.038 -0.348 -0.062                                   
scl(lg,s=F) -0.003 -0.304  0.073      -0.225                       
scl(sD,s=F) -0.004  0.069 -0.003      -0.040     -0.263            
scl(tm,s=F)  0.004  0.229 -0.005      -0.039     -0.118      -0.046
