First, I ran the models with on Age as a random and fixed effect. None of the models converged properly. I already suspected this would happen because the models weren’t converging when we add the predictors. I had been modeling the intercept as a random effect
## Warning in checkConv(attr(opt, "derivs"), opt$par, ctrl =
## control$checkConv, : Model failed to converge with max|grad| = 0.0300648
## (tol = 0.002, component 1)## Warning in checkConv(attr(opt, "derivs"), opt$par, ctrl =
## control$checkConv, : Model failed to converge with max|grad| = 0.00586908
## (tol = 0.002, component 1)## Warning in checkConv(attr(opt, "derivs"), opt$par, ctrl =
## control$checkConv, : Model failed to converge with max|grad| = 0.0369218
## (tol = 0.002, component 1)## Warning in checkConv(attr(opt, "derivs"), opt$par, ctrl =
## control$checkConv, : Model failed to converge with max|grad| = 0.00642891
## (tol = 0.002, component 1)## Warning in checkConv(attr(opt, "derivs"), opt$par, ctrl =
## control$checkConv, : Model failed to converge with max|grad| = 0.0139171
## (tol = 0.002, component 1)## boundary (singular) fit: see ?isSingular
## boundary (singular) fit: see ?isSingular## Warning in checkConv(attr(opt, "derivs"), opt$par, ctrl =
## control$checkConv, : Model failed to converge with max|grad| = 0.0134041
## (tol = 0.002, component 1)## boundary (singular) fit: see ?isSingular## Warning in checkConv(attr(opt, "derivs"), opt$par, ctrl =
## control$checkConv, : Model failed to converge with max|grad| = 0.00842828
## (tol = 0.002, component 1)## Warning in checkConv(attr(opt, "derivs"), opt$par, ctrl =
## control$checkConv, : Model failed to converge with max|grad| = 0.00206442
## (tol = 0.002, component 1)## DigitSpanFwd_valid DigitSpanBck_valid LogTrailsA LogTrailsB
## (Intercept) 7.15*** 5.48*** 3.55*** 4.78***
## cenAge -0.02*** -0.02*** 0.01*** 0.02***
## FluencyWord_valid BVRtot_valid LogBVR CVLtca_valid
## (Intercept) 18.72*** 8.07*** 1.97*** 21.08***
## cenAge -0.05*** 0.18*** 0.02*** -0.26***
## CVLfrl_valid CVLfrs_valid Attention_valid
## (Intercept) 6.06*** 6.00*** 6.41***
## cenAge -0.11*** -0.12*** -0.03***
##
##
## *********************** DigitSpanFwd_valid ***********************
##
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: as.formula(merForm)
## Data: dat
## Control: ..1
##
## REML criterion at convergence: 17004.6
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -2.27136 -0.47467 -0.07056 0.43118 2.87479
##
## Random effects:
## Groups Name Variance Std.Dev. Corr
## HNDid (Intercept) 3.272e+00 1.808823
## cenAge 3.141e-05 0.005604 -1.00
## Residual 1.507e+00 1.227477
## Number of obs: 4060, groups: HNDid, 2630
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 7.148e+00 4.135e-02 2.316e+03 172.858 < 2e-16 ***
## cenAge -1.978e-02 4.033e-03 3.497e+03 -4.903 9.85e-07 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr)
## cenAge 0.165
## convergence code: 0
## Model failed to converge with max|grad| = 0.0300648 (tol = 0.002, component 1)
##
##
##
## *********************** DigitSpanBck_valid ***********************
##
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: as.formula(merForm)
## Data: dat
## Control: ..1
##
## REML criterion at convergence: 16829.5
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.2976 -0.4149 -0.0695 0.4214 3.8961
##
## Random effects:
## Groups Name Variance Std.Dev. Corr
## HNDid (Intercept) 3.0019 1.73259
## cenAge 0.0018 0.04243 -0.19
## Residual 1.4868 1.21934
## Number of obs: 4035, groups: HNDid, 2620
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 5.482e+00 4.063e-02 2.349e+03 134.929 < 2e-16 ***
## cenAge -2.007e-02 4.086e-03 1.422e+03 -4.912 1.01e-06 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr)
## cenAge 0.138
## convergence code: 0
## Model failed to converge with max|grad| = 0.00586908 (tol = 0.002, component 1)
##
##
##
## *********************** LogTrailsA ***********************
##
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: as.formula(merForm)
## Data: dat
## Control: ..1
##
## REML criterion at convergence: 4744.1
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -4.8297 -0.4305 -0.0597 0.3453 7.1791
##
## Random effects:
## Groups Name Variance Std.Dev. Corr
## HNDid (Intercept) 0.1093565 0.33069
## cenAge 0.0001731 0.01316 0.60
## Residual 0.0911702 0.30194
## Number of obs: 4273, groups: HNDid, 2674
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 3.554e+00 8.567e-03 2.066e+03 414.85 <2e-16 ***
## cenAge 1.327e-02 8.336e-04 1.366e+03 15.92 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr)
## cenAge 0.393
## convergence code: 0
## Model failed to converge with max|grad| = 0.0369218 (tol = 0.002, component 1)
##
##
##
## *********************** LogTrailsB ***********************
##
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: as.formula(merForm)
## Data: dat
## Control: ..1
##
## REML criterion at convergence: 8581.9
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.1996 -0.4148 -0.1015 0.3383 3.3582
##
## Random effects:
## Groups Name Variance Std.Dev. Corr
## HNDid (Intercept) 4.301e-01 0.65579
## cenAge 4.747e-05 0.00689 0.82
## Residual 1.603e-01 0.40032
## Number of obs: 4259, groups: HNDid, 2667
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 4.781e+00 1.467e-02 2.238e+03 325.89 <2e-16 ***
## cenAge 2.050e-02 1.353e-03 1.509e+03 15.15 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr)
## cenAge 0.306
## convergence code: 0
## Model failed to converge with max|grad| = 0.00642891 (tol = 0.002, component 1)
##
##
##
## *********************** FluencyWord_valid ***********************
##
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: as.formula(merForm)
## Data: dat
## Control: ..1
##
## REML criterion at convergence: 25558.2
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.1690 -0.5005 -0.0384 0.4437 3.0079
##
## Random effects:
## Groups Name Variance Std.Dev. Corr
## HNDid (Intercept) 18.738924 4.32885
## cenAge 0.001067 0.03267 -1.00
## Residual 8.977242 2.99620
## Number of obs: 4299, groups: HNDid, 2683
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 1.872e+01 9.729e-02 2.491e+03 192.380 < 2e-16 ***
## cenAge -5.036e-02 9.595e-03 3.634e+03 -5.248 1.62e-07 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr)
## cenAge 0.090
## convergence code: 0
## Model failed to converge with max|grad| = 0.0139171 (tol = 0.002, component 1)
##
##
##
## *********************** BVRtot_valid ***********************
##
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: as.formula(merForm)
## Data: dat
## Control: ..1
##
## REML criterion at convergence: 24887.5
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.9303 -0.4839 -0.0672 0.4407 4.5770
##
## Random effects:
## Groups Name Variance Std.Dev. Corr
## HNDid (Intercept) 1.482e+01 3.84937
## cenAge 8.386e-04 0.02896 1.00
## Residual 1.076e+01 3.28003
## Number of obs: 4206, groups: HNDid, 2656
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 8.075e+00 9.411e-02 2.179e+03 85.80 <2e-16 ***
## cenAge 1.818e-01 9.101e-03 3.246e+03 19.98 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr)
## cenAge 0.290
## convergence code: 0
## boundary (singular) fit: see ?isSingular
##
##
##
## *********************** LogBVR ***********************
##
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: as.formula(merForm)
## Data: dat
## Control: ..1
##
## REML criterion at convergence: 9264.9
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.2325 -0.3382 0.1456 0.5298 2.4518
##
## Random effects:
## Groups Name Variance Std.Dev. Corr
## HNDid (Intercept) 2.040e-01 0.45167
## cenAge 9.389e-05 0.00969 -1.00
## Residual 3.394e-01 0.58260
## Number of obs: 4206, groups: HNDid, 2656
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 1.968e+00 1.287e-02 2.482e+03 152.91 <2e-16 ***
## cenAge 2.466e-02 1.364e-03 3.046e+03 18.07 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr)
## cenAge 0.027
## convergence code: 0
## boundary (singular) fit: see ?isSingular
##
##
##
## *********************** CVLtca_valid ***********************
##
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: as.formula(merForm)
## Data: dat
## Control: ..1
##
## REML criterion at convergence: 24991.6
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -2.70695 -0.54035 -0.00386 0.54855 2.42084
##
## Random effects:
## Groups Name Variance Std.Dev. Corr
## HNDid (Intercept) 24.212779 4.92065
## cenAge 0.002912 0.05396 -0.42
## Residual 24.589877 4.95882
## Number of obs: 3761, groups: HNDid, 2526
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 21.08334 0.13096 2155.83644 161.00 <2e-16 ***
## cenAge -0.25638 0.01347 1302.42346 -19.03 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr)
## cenAge 0.140
## convergence code: 0
## Model failed to converge with max|grad| = 0.0134041 (tol = 0.002, component 1)
##
##
##
## *********************** CVLfrl_valid ***********************
##
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: as.formula(merForm)
## Data: dat
## Control: ..1
##
## REML criterion at convergence: 18351.3
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -2.63021 -0.53023 -0.02366 0.51552 2.46430
##
## Random effects:
## Groups Name Variance Std.Dev. Corr
## HNDid (Intercept) 5.342e+00 2.31127
## cenAge 7.242e-05 0.00851 -1.00
## Residual 4.188e+00 2.04641
## Number of obs: 3686, groups: HNDid, 2491
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 6.06271 0.05894 2158.52990 102.87 <2e-16 ***
## cenAge -0.11364 0.00599 2948.16532 -18.97 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr)
## cenAge 0.149
## convergence code: 0
## boundary (singular) fit: see ?isSingular
##
##
##
## *********************** CVLfrs_valid ***********************
##
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: as.formula(merForm)
## Data: dat
## Control: ..1
##
## REML criterion at convergence: 18349.3
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -2.63905 -0.53843 -0.01732 0.50769 2.48873
##
## Random effects:
## Groups Name Variance Std.Dev. Corr
## HNDid (Intercept) 5.055941 2.24854
## cenAge 0.001253 0.03539 -0.18
## Residual 4.167500 2.04145
## Number of obs: 3699, groups: HNDid, 2499
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 5.997e+00 5.814e-02 2.166e+03 103.14 <2e-16 ***
## cenAge -1.150e-01 5.952e-03 1.294e+03 -19.33 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr)
## cenAge 0.156
## convergence code: 0
## Model failed to converge with max|grad| = 0.00842828 (tol = 0.002, component 1)
##
##
##
## *********************** Attention_valid ***********************
##
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: as.formula(merForm)
## Data: dat
## Control: ..1
##
## REML criterion at convergence: 15896.5
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.2011 -0.5030 0.0275 0.5181 3.0114
##
## Random effects:
## Groups Name Variance Std.Dev. Corr
## HNDid (Intercept) 2.688832 1.63977
## cenAge 0.001596 0.03995 0.22
## Residual 1.993102 1.41177
## Number of obs: 3725, groups: HNDid, 2487
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 6.414e+00 4.229e-02 2.141e+03 151.656 < 2e-16 ***
## cenAge -2.784e-02 4.235e-03 1.399e+03 -6.573 6.93e-11 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr)
## cenAge 0.236
## convergence code: 0
## Model failed to converge with max|grad| = 0.00206442 (tol = 0.002, component 1)Next, I ran the models with on Time as a random and fixed effect. More of the models converged, but several didn’t.
## boundary (singular) fit: see ?isSingular
## boundary (singular) fit: see ?isSingular
## boundary (singular) fit: see ?isSingular## Warning in checkConv(attr(opt, "derivs"), opt$par, ctrl =
## control$checkConv, : Model failed to converge with max|grad| = 0.00418018
## (tol = 0.002, component 1)## Warning in checkConv(attr(opt, "derivs"), opt$par, ctrl =
## control$checkConv, : Model failed to converge with max|grad| = 0.0645692
## (tol = 0.002, component 1)## boundary (singular) fit: see ?isSingular
## boundary (singular) fit: see ?isSingular
## boundary (singular) fit: see ?isSingular## DigitSpanFwd_valid DigitSpanBck_valid LogTrailsA LogTrailsB
## (Intercept) 7.19*** 5.53*** 3.53*** 4.74***
## cenTime -0.01 -0.02 0.01** 0.02***
## FluencyWord_valid BVRtot_valid LogBVR CVLtca_valid
## (Intercept) 18.82*** 7.68*** 1.92*** 21.72***
## cenTime 0.03 0.43*** 0.08*** -1.15***
## CVLfrl_valid CVLfrs_valid Attention_valid
## (Intercept) 6.33*** 6.27*** 6.47***
## cenTime -0.38*** -0.36*** -0.05***
##
##
## *********************** DigitSpanFwd_valid ***********************
##
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: as.formula(merForm)
## Data: dat
## Control: ..1
##
## REML criterion at convergence: 17027.4
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -2.32591 -0.47888 -0.05506 0.45147 2.83677
##
## Random effects:
## Groups Name Variance Std.Dev. Corr
## HNDid (Intercept) 3.3677614 1.83515
## cenTime 0.0001259 0.01122 1.00
## Residual 1.5029957 1.22597
## Number of obs: 4060, groups: HNDid, 2630
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 7.190e+00 4.107e-02 2.600e+03 175.058 <2e-16 ***
## cenTime -1.144e-02 9.192e-03 1.815e+03 -1.244 0.214
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr)
## cenTime 0.051
## convergence code: 0
## boundary (singular) fit: see ?isSingular
##
##
##
## *********************** DigitSpanBck_valid ***********************
##
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: as.formula(merForm)
## Data: dat
## Control: ..1
##
## REML criterion at convergence: 16859.7
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.3681 -0.3990 -0.0658 0.4113 3.8363
##
## Random effects:
## Groups Name Variance Std.Dev. Corr
## HNDid (Intercept) 3.2368666 1.79913
## cenTime 0.0003629 0.01905 -1.00
## Residual 1.5055774 1.22702
## Number of obs: 4035, groups: HNDid, 2620
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 5.527e+00 4.053e-02 2.575e+03 136.362 <2e-16 ***
## cenTime -1.770e-02 9.182e-03 1.831e+03 -1.928 0.054 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr)
## cenTime -0.015
## convergence code: 0
## boundary (singular) fit: see ?isSingular
##
##
##
## *********************** LogTrailsA ***********************
##
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: as.formula(merForm)
## Data: dat
## Control: ..1
##
## REML criterion at convergence: 5044
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -4.4990 -0.4141 -0.0537 0.3347 6.9508
##
## Random effects:
## Groups Name Variance Std.Dev. Corr
## HNDid (Intercept) 1.308e-01 0.361610
## cenTime 8.367e-05 0.009147 1.00
## Residual 9.164e-02 0.302726
## Number of obs: 4273, groups: HNDid, 2674
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 3.530e+00 8.490e-03 2.507e+03 415.782 < 2e-16 ***
## cenTime 6.834e-03 2.151e-03 1.935e+03 3.178 0.00151 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr)
## cenTime 0.082
## convergence code: 0
## boundary (singular) fit: see ?isSingular
##
##
##
## *********************** LogTrailsB ***********************
##
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: as.formula(merForm)
## Data: dat
## Control: ..1
##
## REML criterion at convergence: 8740.6
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.0908 -0.2999 -0.0697 0.2526 3.3743
##
## Random effects:
## Groups Name Variance Std.Dev. Corr
## HNDid (Intercept) 0.486374 0.69741
## cenTime 0.006696 0.08183 0.11
## Residual 0.089221 0.29870
## Number of obs: 4259, groups: HNDid, 2667
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 4.740e+00 1.453e-02 2.622e+03 326.174 < 2e-16 ***
## cenTime 1.930e-02 2.977e-03 1.769e+03 6.484 1.16e-10 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr)
## cenTime 0.076
## convergence code: 0
## Model failed to converge with max|grad| = 0.00418018 (tol = 0.002, component 1)
##
##
##
## *********************** FluencyWord_valid ***********************
##
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: as.formula(merForm)
## Data: dat
## Control: ..1
##
## REML criterion at convergence: 25598
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -2.96183 -0.46513 -0.03612 0.41635 2.81427
##
## Random effects:
## Groups Name Variance Std.Dev. Corr
## HNDid (Intercept) 20.23566 4.4984
## cenTime 0.07715 0.2778 -0.06
## Residual 8.06944 2.8407
## Number of obs: 4299, groups: HNDid, 2683
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 1.882e+01 9.825e-02 2.678e+03 191.597 <2e-16 ***
## cenTime 3.389e-02 2.143e-02 1.770e+03 1.581 0.114
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr)
## cenTime -0.010
##
##
## *********************** BVRtot_valid ***********************
##
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: as.formula(merForm)
## Data: dat
## Control: ..1
##
## REML criterion at convergence: 24875.7
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -2.20277 -0.29619 -0.03407 0.26133 2.62348
##
## Random effects:
## Groups Name Variance Std.Dev. Corr
## HNDid (Intercept) 19.503 4.4163
## cenTime 0.574 0.7576 -0.06
## Residual 3.586 1.8938
## Number of obs: 4206, groups: HNDid, 2656
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 7.682e+00 9.361e-02 2.587e+03 82.06 <2e-16 ***
## cenTime 4.256e-01 2.293e-02 1.916e+03 18.56 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr)
## cenTime -0.012
##
##
## *********************** LogBVR ***********************
##
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: as.formula(merForm)
## Data: dat
## Control: ..1
##
## REML criterion at convergence: 8887.7
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.0644 -0.2782 0.0967 0.3545 2.6882
##
## Random effects:
## Groups Name Variance Std.Dev. Corr
## HNDid (Intercept) 0.35215 0.5934
## cenTime 0.01561 0.1249 -0.60
## Residual 0.13444 0.3667
## Number of obs: 4206, groups: HNDid, 2656
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 1.920e+00 1.334e-02 2.566e+03 143.90 <2e-16 ***
## cenTime 7.702e-02 3.819e-03 2.188e+03 20.17 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr)
## cenTime -0.370
## convergence code: 0
## Model failed to converge with max|grad| = 0.0645692 (tol = 0.002, component 1)
##
##
##
## *********************** CVLtca_valid ***********************
##
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: as.formula(merForm)
## Data: dat
## Control: ..1
##
## REML criterion at convergence: 24320
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -2.50114 -0.47944 -0.02306 0.48124 2.47035
##
## Random effects:
## Groups Name Variance Std.Dev. Corr
## HNDid (Intercept) 30.306430 5.50513
## cenTime 0.003695 0.06078 1.00
## Residual 15.189280 3.89734
## Number of obs: 3761, groups: HNDid, 2526
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 21.72249 0.12815 2481.65496 169.50 <2e-16 ***
## cenTime -1.15313 0.03088 1708.68173 -37.34 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr)
## cenTime -0.002
## convergence code: 0
## boundary (singular) fit: see ?isSingular
##
##
##
## *********************** CVLfrl_valid ***********************
##
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: as.formula(merForm)
## Data: dat
## Control: ..1
##
## REML criterion at convergence: 18122.4
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -2.60658 -0.48928 -0.03341 0.48927 2.49931
##
## Random effects:
## Groups Name Variance Std.Dev. Corr
## HNDid (Intercept) 6.1699792 2.48394
## cenTime 0.0001409 0.01187 1.00
## Residual 3.3422222 1.82817
## Number of obs: 3686, groups: HNDid, 2491
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 6.33087 0.05890 2438.91523 107.48 <2e-16 ***
## cenTime -0.38192 0.01461 1695.01151 -26.14 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr)
## cenTime -0.026
## convergence code: 0
## boundary (singular) fit: see ?isSingular
##
##
##
## *********************** CVLfrs_valid ***********************
##
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: as.formula(merForm)
## Data: dat
## Control: ..1
##
## REML criterion at convergence: 18187.7
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -2.40502 -0.47576 -0.01688 0.49652 2.53422
##
## Random effects:
## Groups Name Variance Std.Dev. Corr
## HNDid (Intercept) 6.020e+00 2.453510
## cenTime 1.876e-05 0.004331 1.00
## Residual 3.426e+00 1.850874
## Number of obs: 3699, groups: HNDid, 2499
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 6.2692 0.0585 2440.9147 107.16 <2e-16 ***
## cenTime -0.3650 0.0147 1715.3717 -24.83 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr)
## cenTime -0.038
## convergence code: 0
## boundary (singular) fit: see ?isSingular
##
##
##
## *********************** Attention_valid ***********************
##
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: as.formula(merForm)
## Data: dat
## Control: ..1
##
## REML criterion at convergence: 15920.3
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.2066 -0.4654 0.0242 0.5259 2.8922
##
## Random effects:
## Groups Name Variance Std.Dev. Corr
## HNDid (Intercept) 2.834399 1.684
## cenTime 0.004096 0.064 0.09
## Residual 1.957670 1.399
## Number of obs: 3725, groups: HNDid, 2487
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 6.47227 0.04139 2433.89171 156.36 < 2e-16 ***
## cenTime -0.05215 0.01093 1530.95196 -4.77 2.01e-06 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr)
## cenTime -0.014I’m not sure what the best next steps are. Maybe the 3 of us can discuss it briefly during our meeting on Tuesday?