RE_COVID_Initial
Rick Reneau
August 14, 2020
PA ~ RE Pre-COVID
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: PA_avg ~ roaming_entropy + time_of_day + precipi + mean_temp +
## distance + dow + (1 | subject)
## Data: df[which(df$lockdown == 0), ]
##
## REML criterion at convergence: 41650.9
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.9243 -0.5331 0.0465 0.6093 3.4187
##
## Random effects:
## Groups Name Variance Std.Dev.
## subject (Intercept) 111.7 10.57
## Residual 294.4 17.16
## Number of obs: 4826, groups: subject, 251
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 63.557370 2.613406 4670.431042 24.320 < 2e-16 ***
## roaming_entropy 0.622125 0.303622 4743.966238 2.049 0.040516 *
## time_of_day 0.040150 0.014628 4621.874974 2.745 0.006081 **
## precipi 1.933098 1.770036 4610.655066 1.092 0.274836
## mean_temp -0.147603 0.031175 4692.538551 -4.735 0.000002259 ***
## distance 0.002097 0.000716 4624.696719 2.930 0.003411 **
## dowMonday -3.517568 1.027297 4588.652966 -3.424 0.000622 ***
## dowSaturday 5.211242 1.044068 4590.837985 4.991 0.000000622 ***
## dowSunday -1.102697 1.029303 4595.748201 -1.071 0.284089
## dowThursday -3.505592 0.972934 4582.232944 -3.603 0.000318 ***
## dowTuesday -7.917715 0.931007 4589.355944 -8.504 < 2e-16 ***
## dowWednesday -4.325523 0.973888 4580.325197 -4.441 0.000009144 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) rmng_n tm_f_d precip mn_tmp distnc dwMndy dwStrd dwSndy
## romng_ntrpy -0.241
## time_of_day -0.166 0.019
## precipi -0.079 0.040 0.022
## mean_temp -0.855 -0.070 -0.008 -0.054
## distance -0.030 -0.224 0.005 -0.014 0.088
## dowMonday -0.463 0.049 0.031 0.201 0.272 0.026
## dowSaturday -0.170 0.119 -0.004 0.157 -0.068 -0.047 0.475
## dowSunday -0.408 0.208 -0.006 0.163 0.170 -0.086 0.553 0.491
## dowThursday -0.261 0.041 -0.002 0.218 0.038 0.003 0.546 0.515 0.536
## dowTuesday -0.413 0.026 -0.011 0.093 0.223 0.022 0.593 0.506 0.569
## dowWednesdy -0.278 0.039 0.002 0.223 0.057 0.003 0.550 0.512 0.538
## dwThrs dwTsdy
## romng_ntrpy
## time_of_day
## precipi
## mean_temp
## distance
## dowMonday
## dowSaturday
## dowSunday
## dowThursday
## dowTuesday 0.570
## dowWednesdy 0.563 0.571
## fit warnings:
## Some predictor variables are on very different scales: consider rescaling## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: PA_avg ~ roaming_entropy + dow + (1 | subject)
## Data: df[which(df$lockdown == 0), ]
##
## REML criterion at convergence: 41670.9
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -4.0272 -0.5305 0.0428 0.6062 3.3341
##
## Random effects:
## Groups Name Variance Std.Dev.
## subject (Intercept) 112.3 10.60
## Residual 296.7 17.23
## Number of obs: 4826, groups: subject, 251
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 54.05200 1.23733 1685.40030 43.684 < 2e-16 ***
## roaming_entropy 0.72019 0.29642 4744.28947 2.430 0.015153 *
## dowMonday -2.47259 0.96683 4584.48221 -2.557 0.010577 *
## dowSaturday 4.90563 1.03238 4592.34180 4.752 2.08e-06 ***
## dowSunday -0.05831 0.99731 4595.01955 -0.058 0.953375
## dowThursday -3.50035 0.95195 4586.04687 -3.677 0.000239 ***
## dowTuesday -7.00127 0.90576 4587.48237 -7.730 1.32e-14 ***
## dowWednesday -4.24039 0.95079 4582.31865 -4.460 8.40e-06 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) rmng_n dwMndy dwStrd dwSndy dwThrs dwTsdy
## romng_ntrpy -0.618
## dowMonday -0.450 0.066
## dowSaturday -0.448 0.105 0.498
## dowSunday -0.522 0.204 0.520 0.497
## dowThursday -0.439 0.038 0.534 0.504 0.522
## dowTuesday -0.463 0.041 0.561 0.529 0.549 0.570
## dowWednesdy -0.438 0.036 0.533 0.502 0.521 0.540 0.567PA ~ NL Pre_COVID
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: PA_avg ~ novel_locations + time_of_day + precipi + mean_temp +
## distance + dow + (1 | subject)
## Data: df[which(df$lockdown == 0), ]
##
## REML criterion at convergence: 39616.8
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.8798 -0.5304 0.0507 0.6156 3.4694
##
## Random effects:
## Groups Name Variance Std.Dev.
## subject (Intercept) 108.5 10.42
## Residual 291.4 17.07
## Number of obs: 4594, groups: subject, 249
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 61.8175174 2.6014142 4454.4355737 23.763 < 2e-16 ***
## novel_locations 0.0286850 0.0047144 4481.7217276 6.085 1.27e-09 ***
## time_of_day 0.0479237 0.0149239 4394.4844406 3.211 0.001331 **
## precipi 1.8103321 1.7820815 4384.6142583 1.016 0.309756
## mean_temp -0.1283149 0.0313610 4469.8918309 -4.092 4.36e-05 ***
## distance 0.0007938 0.0007410 4409.0524697 1.071 0.284140
## dowMonday -2.5607596 1.0732482 4361.4498928 -2.386 0.017076 *
## dowSaturday 4.7744618 1.0597375 4357.3001669 4.505 6.80e-06 ***
## dowSunday -0.9926783 1.0383992 4360.0896535 -0.956 0.339141
## dowThursday -3.2934031 1.0056530 4354.7604672 -3.275 0.001065 **
## dowTuesday -7.2862356 0.9655927 4365.9010052 -7.546 5.44e-14 ***
## dowWednesday -3.7903010 1.0211630 4353.4114705 -3.712 0.000208 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) nvl_lc tm_f_d precip mn_tmp distnc dwMndy dwStrd dwSndy
## novel_lctns -0.199
## time_of_day -0.167 0.003
## precipi -0.081 0.023 0.021
## mean_temp -0.893 0.089 -0.003 -0.054
## distance -0.014 -0.340 0.008 -0.011 0.039
## dowMonday -0.474 0.110 0.036 0.211 0.270 -0.004
## dowSaturday -0.150 -0.018 -0.008 0.173 -0.067 -0.012 0.483
## dowSunday -0.392 0.100 -0.013 0.181 0.186 -0.071 0.570 0.500
## dowThursday -0.272 0.079 -0.004 0.235 0.036 -0.015 0.559 0.533 0.562
## dowTuesday -0.435 0.136 -0.009 0.115 0.219 -0.019 0.606 0.522 0.600
## dowWednesdy -0.293 0.080 -0.001 0.233 0.063 -0.019 0.556 0.522 0.558
## dwThrs dwTsdy
## novel_lctns
## time_of_day
## precipi
## mean_temp
## distance
## dowMonday
## dowSaturday
## dowSunday
## dowThursday
## dowTuesday 0.591
## dowWednesdy 0.575 0.584
## fit warnings:
## Some predictor variables are on very different scales: consider rescaling## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: PA_avg ~ novel_locations + dow + (1 | subject)
## Data: df[which(df$lockdown == 0), ]
##
## REML criterion at convergence: 39624.4
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.9377 -0.5274 0.0471 0.6145 3.3998
##
## Random effects:
## Groups Name Variance Std.Dev.
## subject (Intercept) 108.8 10.43
## Residual 293.0 17.12
## Number of obs: 4594, groups: subject, 249
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 53.905965 1.035147 988.406262 52.076 < 2e-16 ***
## novel_locations 0.032212 0.004418 4471.170362 7.291 3.61e-13 ***
## dowMonday -1.657958 1.006525 4354.882321 -1.647 0.099587 .
## dowSaturday 4.392322 1.044728 4359.466973 4.204 2.67e-05 ***
## dowSunday -0.210766 1.000153 4357.080986 -0.211 0.833105
## dowThursday -3.289092 0.978782 4357.309943 -3.360 0.000785 ***
## dowTuesday -6.452577 0.936310 4361.290879 -6.891 6.31e-12 ***
## dowWednesday -3.676834 0.992490 4354.407092 -3.705 0.000214 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) nvl_lc dwMndy dwStrd dwSndy dwThrs dwTsdy
## novel_lctns -0.294
## dowMonday -0.534 0.086
## dowSaturday -0.486 -0.021 0.504
## dowSunday -0.531 0.058 0.530 0.507
## dowThursday -0.546 0.071 0.546 0.519 0.546
## dowTuesday -0.584 0.115 0.573 0.541 0.573 0.589
## dowWednesdy -0.536 0.067 0.536 0.510 0.537 0.549 0.575RE ~ Lockdown
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: roaming_entropy ~ lockdown + time_of_day + precipi + mean_temp +
## distance + dow + (1 | subject)
## Data: df
##
## REML criterion at convergence: 18641.3
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -4.8348 -0.6179 0.0793 0.6454 5.1186
##
## Random effects:
## Groups Name Variance Std.Dev.
## subject (Intercept) 0.08582 0.2929
## Residual 0.60872 0.7802
## Number of obs: 7753, groups: subject, 253
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 2.21786652 0.07546790 5399.99653015 29.388 < 2e-16 ***
## lockdown -1.37954466 0.02011854 7711.86125867 -68.571 < 2e-16 ***
## time_of_day -0.00087166 0.00052184 7582.93613988 -1.670 0.094891 .
## precipi -0.03893910 0.04380624 7553.54393056 -0.889 0.374088
## mean_temp 0.00355873 0.00091914 6969.35694737 3.872 0.000109 ***
## distance 0.00054505 0.00003115 7590.00753956 17.500 < 2e-16 ***
## dowMonday -0.14759023 0.03433725 7551.59721678 -4.298 0.0000174 ***
## dowSaturday -0.11893190 0.03550144 7529.99681236 -3.350 0.000812 ***
## dowSunday -0.45553383 0.03530311 7532.20017698 -12.904 < 2e-16 ***
## dowThursday -0.05585909 0.03386655 7524.40620754 -1.649 0.099110 .
## dowTuesday -0.05041249 0.03356106 7535.92899443 -1.502 0.133110
## dowWednesday -0.08757940 0.03425624 7520.25490578 -2.557 0.010590 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) lckdwn tm_f_d precip mn_tmp distnc dwMndy dwStrd dwSndy
## lockdown -0.295
## time_of_day -0.210 0.006
## precipi -0.018 -0.200 0.021
## mean_temp -0.879 0.249 0.004 -0.049
## distance -0.067 0.112 0.009 0.000 0.039
## dowMonday -0.385 0.001 0.035 0.053 0.153 0.019
## dowSaturday -0.227 -0.036 -0.001 -0.042 0.001 -0.017 0.513
## dowSunday -0.315 0.019 -0.010 0.016 0.093 -0.041 0.531 0.500
## dowThursday -0.265 -0.029 -0.003 0.100 0.018 0.008 0.548 0.518 0.527
## dowTuesday -0.351 0.079 -0.004 -0.032 0.116 0.016 0.558 0.525 0.538
## dowWednesdy -0.270 0.006 0.002 0.046 0.028 0.008 0.539 0.512 0.520
## dwThrs dwTsdy
## lockdown
## time_of_day
## precipi
## mean_temp
## distance
## dowMonday
## dowSaturday
## dowSunday
## dowThursday
## dowTuesday 0.550
## dowWednesdy 0.544 0.545
## fit warnings:
## Some predictor variables are on very different scales: consider rescaling## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: roaming_entropy ~ lockdown + dow + (1 | subject)
## Data: df
##
## REML criterion at convergence: 53526.8
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.8403 -0.6337 0.0284 0.6205 8.4065
##
## Random effects:
## Groups Name Variance Std.Dev.
## subject (Intercept) 0.1156 0.3401
## Residual 0.6932 0.8326
## Number of obs: 21369, groups: subject, 258
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 2.50470 0.02662 516.19037 94.077 < 2e-16 ***
## lockdown -1.27575 0.01190 21334.61677 -107.235 < 2e-16 ***
## dowMonday -0.18135 0.02137 21111.43889 -8.486 < 2e-16 ***
## dowSaturday -0.18942 0.02166 21111.34791 -8.746 < 2e-16 ***
## dowSunday -0.41955 0.02152 21113.94144 -19.497 < 2e-16 ***
## dowThursday -0.07784 0.02104 21111.51043 -3.699 0.000217 ***
## dowTuesday -0.15346 0.02107 21112.98565 -7.283 3.38e-13 ***
## dowWednesday -0.11672 0.02111 21111.58753 -5.528 3.27e-08 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) lckdwn dwMndy dwStrd dwSndy dwThrs dwTsdy
## lockdown -0.179
## dowMonday -0.395 -0.006
## dowSaturday -0.386 -0.023 0.487
## dowSunday -0.395 0.008 0.490 0.483
## dowThursday -0.400 -0.010 0.501 0.495 0.497
## dowTuesday -0.402 0.000 0.500 0.494 0.497 0.508
## dowWednesdy -0.402 0.004 0.499 0.492 0.496 0.507 0.506NL ~ Lockdown
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: novel_locations ~ lockdown + time_of_day + precipi + mean_temp +
## distance + dow + (1 | subject)
## Data: df
##
## REML criterion at convergence: 79500.4
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -8.6285 -0.5126 -0.1831 0.2609 13.2830
##
## Random effects:
## Groups Name Variance Std.Dev.
## subject (Intercept) 198.8 14.10
## Residual 2198.6 46.89
## Number of obs: 7519, groups: subject, 249
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 78.611456 4.459834 4847.185721 17.627 < 2e-16 ***
## lockdown -34.021748 1.215104 7505.242271 -27.999 < 2e-16 ***
## time_of_day -0.003031 0.031810 7374.672773 -0.095 0.924096
## precipi -2.180774 2.637353 7343.532036 -0.827 0.408332
## mean_temp -0.270487 0.054684 5645.313114 -4.946 7.78e-07 ***
## distance 0.056120 0.001876 7391.240283 29.921 < 2e-16 ***
## dowMonday -13.781707 2.115396 7332.440214 -6.515 7.75e-11 ***
## dowSaturday 7.183744 2.164039 7304.876243 3.320 0.000906 ***
## dowSunday -12.051352 2.157280 7310.531725 -5.586 2.40e-08 ***
## dowThursday -8.204777 2.075927 7300.711055 -3.952 7.81e-05 ***
## dowTuesday -16.635046 2.055771 7313.381439 -8.092 6.83e-16 ***
## dowWednesday -9.916710 2.120360 7295.825704 -4.677 2.96e-06 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) lckdwn tm_f_d precip mn_tmp distnc dwMndy dwStrd dwSndy
## lockdown -0.300
## time_of_day -0.215 0.004
## precipi -0.021 -0.195 0.021
## mean_temp -0.882 0.246 0.004 -0.050
## distance -0.069 0.115 0.008 0.001 0.040
## dowMonday -0.388 -0.001 0.038 0.055 0.141 0.017
## dowSaturday -0.239 -0.028 -0.002 -0.037 -0.004 -0.017 0.521
## dowSunday -0.324 0.024 -0.013 0.021 0.086 -0.040 0.537 0.512
## dowThursday -0.273 -0.023 -0.005 0.103 0.011 0.008 0.554 0.530 0.538
## dowTuesday -0.358 0.083 -0.003 -0.027 0.105 0.016 0.562 0.537 0.548
## dowWednesdy -0.279 0.005 0.000 0.047 0.025 0.006 0.540 0.519 0.526
## dwThrs dwTsdy
## lockdown
## time_of_day
## precipi
## mean_temp
## distance
## dowMonday
## dowSaturday
## dowSunday
## dowThursday
## dowTuesday 0.560
## dowWednesdy 0.549 0.550
## fit warnings:
## Some predictor variables are on very different scales: consider rescaling## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: novel_locations ~ lockdown + dow + (1 | subject)
## Data: df
##
## REML criterion at convergence: 212395.1
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -2.0767 -0.5183 -0.2060 0.2239 18.3149
##
## Random effects:
## Groups Name Variance Std.Dev.
## subject (Intercept) 288.8 16.99
## Residual 2817.9 53.08
## Number of obs: 19652, groups: subject, 254
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 65.0478 1.5097 746.9771 43.088 < 2e-16 ***
## lockdown -29.6016 0.7852 19643.2075 -37.698 < 2e-16 ***
## dowMonday -15.9660 1.4212 19401.6594 -11.234 < 2e-16 ***
## dowSaturday 2.7597 1.4404 19402.7826 1.916 0.0554 .
## dowSunday -8.5579 1.4314 19403.8752 -5.979 0.00000000229 ***
## dowThursday -7.9942 1.3972 19400.3991 -5.721 0.00000001072 ***
## dowTuesday -13.3625 1.4000 19402.1480 -9.545 < 2e-16 ***
## dowWednesday -12.0328 1.4028 19400.6017 -8.578 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) lckdwn dwMndy dwStrd dwSndy dwThrs dwTsdy
## lockdown -0.227
## dowMonday -0.461 -0.008
## dowSaturday -0.451 -0.026 0.486
## dowSunday -0.462 0.008 0.489 0.482
## dowThursday -0.468 -0.010 0.501 0.494 0.497
## dowTuesday -0.471 0.001 0.500 0.493 0.496 0.508
## dowWednesdy -0.470 0.005 0.499 0.492 0.495 0.507 0.506PA ~ Lockdown
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: PA_avg ~ lockdown + time_of_day + precipi + mean_temp + distance +
## dow + (1 | subject)
## Data: df
##
## REML criterion at convergence: 66812.9
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.7505 -0.5570 0.0514 0.6011 4.0606
##
## Random effects:
## Groups Name Variance Std.Dev.
## subject (Intercept) 123.1 11.09
## Residual 297.9 17.26
## Number of obs: 7753, groups: subject, 253
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 55.2533166 1.7993688 4202.6423583 30.707 < 2e-16 ***
## lockdown -6.1871107 0.4480669 7610.6826562 -13.808 < 2e-16 ***
## time_of_day 0.0241138 0.0115688 7531.1857722 2.084 0.037159 *
## precipi -1.8720810 0.9704045 7515.1716223 -1.929 0.053747 .
## mean_temp -0.0130543 0.0209011 7736.6886756 -0.625 0.532269
## distance 0.0027902 0.0006905 7531.5766827 4.041 5.38e-05 ***
## dowMonday -2.5388763 0.7606206 7514.6427501 -3.338 0.000848 ***
## dowSaturday 3.5035114 0.7860270 7505.2806861 4.457 8.42e-06 ***
## dowSunday 0.2051902 0.7817024 7508.4750933 0.262 0.792950
## dowThursday -2.6067522 0.7497389 7503.2754527 -3.477 0.000510 ***
## dowTuesday -4.6947823 0.7431834 7509.5074100 -6.317 2.82e-10 ***
## dowWednesday -2.7102946 0.7582951 7501.2961739 -3.574 0.000354 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) lckdwn tm_f_d precip mn_tmp distnc dwMndy dwStrd dwSndy
## lockdown -0.280
## time_of_day -0.196 0.007
## precipi -0.015 -0.200 0.020
## mean_temp -0.839 0.251 0.005 -0.049
## distance -0.061 0.112 0.009 0.000 0.037
## dowMonday -0.364 0.003 0.035 0.053 0.157 0.019
## dowSaturday -0.210 -0.037 -0.002 -0.043 0.000 -0.017 0.512
## dowSunday -0.297 0.019 -0.010 0.015 0.096 -0.041 0.531 0.500
## dowThursday -0.246 -0.029 -0.004 0.099 0.018 0.008 0.548 0.518 0.527
## dowTuesday -0.331 0.079 -0.004 -0.033 0.119 0.016 0.558 0.525 0.538
## dowWednesdy -0.252 0.006 0.002 0.046 0.028 0.008 0.538 0.512 0.520
## dwThrs dwTsdy
## lockdown
## time_of_day
## precipi
## mean_temp
## distance
## dowMonday
## dowSaturday
## dowSunday
## dowThursday
## dowTuesday 0.550
## dowWednesdy 0.544 0.545
## fit warnings:
## Some predictor variables are on very different scales: consider rescaling## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: PA_avg ~ lockdown + dow + (1 | subject)
## Data: df
##
## REML criterion at convergence: 66814.1
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.7596 -0.5577 0.0455 0.6018 4.0514
##
## Random effects:
## Groups Name Variance Std.Dev.
## subject (Intercept) 123.0 11.09
## Residual 298.8 17.29
## Number of obs: 7753, groups: subject, 253
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 55.0482 0.9109 573.1100 60.434 < 2e-16 ***
## lockdown -6.4777 0.4236 7609.1116 -15.293 < 2e-16 ***
## dowMonday -2.4670 0.7503 7505.7572 -3.288 0.001014 **
## dowSaturday 3.4947 0.7863 7508.9983 4.445 8.94e-06 ***
## dowSunday 0.4408 0.7783 7507.7673 0.566 0.571135
## dowThursday -2.4620 0.7468 7507.8901 -3.296 0.000984 ***
## dowTuesday -4.7083 0.7387 7506.3417 -6.374 1.95e-10 ***
## dowWednesday -2.6488 0.7582 7505.1034 -3.494 0.000479 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) lckdwn dwMndy dwStrd dwSndy dwThrs dwTsdy
## lockdown -0.157
## dowMonday -0.446 -0.029
## dowSaturday -0.422 -0.045 0.523
## dowSunday -0.435 0.004 0.527 0.503
## dowThursday -0.450 -0.016 0.550 0.526 0.529
## dowTuesday -0.466 0.046 0.554 0.528 0.535 0.557
## dowWednesdy -0.447 0.008 0.540 0.515 0.520 0.542 0.548NA ~ Lockdown
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: NA_avg ~ lockdown + time_of_day + precipi + mean_temp + distance +
## dow + (1 | subject)
## Data: df
##
## REML criterion at convergence: 67166.8
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.5853 -0.6257 -0.0664 0.5594 4.4828
##
## Random effects:
## Groups Name Variance Std.Dev.
## subject (Intercept) 208.3 14.43
## Residual 307.3 17.53
## Number of obs: 7753, groups: subject, 253
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 40.3598640 1.9227581 2973.7340300 20.991 < 2e-16 ***
## lockdown 3.8025421 0.4558335 7570.7580217 8.342 < 2e-16 ***
## time_of_day -0.0238897 0.0117555 7515.1508516 -2.032 0.04217 *
## precipi 1.9196759 0.9858470 7503.6677665 1.947 0.05154 .
## mean_temp 0.0119724 0.0213693 7719.1565000 0.560 0.57532
## distance -0.0022198 0.0007017 7514.2214403 -3.163 0.00157 **
## dowMonday 1.2524059 0.7727188 7503.1967918 1.621 0.10511
## dowSaturday -3.1316546 0.7984350 7497.1913075 -3.922 0.000088512 ***
## dowSunday -0.8155057 0.7940847 7500.8703770 -1.027 0.30447
## dowThursday 1.9764571 0.7615585 7496.4907083 2.595 0.00947 **
## dowTuesday 3.7478867 0.7549628 7501.1071802 4.964 0.000000705 ***
## dowWednesday 2.0234321 0.7702299 7495.1191918 2.627 0.00863 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) lckdwn tm_f_d precip mn_tmp distnc dwMndy dwStrd dwSndy
## lockdown -0.267
## time_of_day -0.186 0.007
## precipi -0.014 -0.200 0.020
## mean_temp -0.803 0.251 0.005 -0.049
## distance -0.058 0.112 0.009 0.000 0.037
## dowMonday -0.347 0.003 0.036 0.053 0.158 0.019
## dowSaturday -0.200 -0.037 -0.002 -0.043 0.000 -0.018 0.512
## dowSunday -0.283 0.019 -0.010 0.015 0.096 -0.041 0.531 0.500
## dowThursday -0.234 -0.029 -0.004 0.099 0.018 0.008 0.548 0.519 0.527
## dowTuesday -0.316 0.079 -0.004 -0.033 0.119 0.016 0.558 0.525 0.538
## dowWednesdy -0.240 0.006 0.002 0.046 0.028 0.008 0.538 0.512 0.520
## dwThrs dwTsdy
## lockdown
## time_of_day
## precipi
## mean_temp
## distance
## dowMonday
## dowSaturday
## dowSunday
## dowThursday
## dowTuesday 0.550
## dowWednesdy 0.544 0.545
## fit warnings:
## Some predictor variables are on very different scales: consider rescaling## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: NA_avg ~ lockdown + dow + (1 | subject)
## Data: df
##
## REML criterion at convergence: 67161.6
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.5735 -0.6284 -0.0673 0.5554 4.5122
##
## Random effects:
## Groups Name Variance Std.Dev.
## subject (Intercept) 208.5 14.44
## Residual 307.9 17.55
## Number of obs: 7753, groups: subject, 253
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 40.5399 1.0871 436.9273 37.291 < 2e-16 ***
## lockdown 4.0654 0.4307 7571.0567 9.439 < 2e-16 ***
## dowMonday 1.1761 0.7618 7498.7955 1.544 0.1227
## dowSaturday -3.1100 0.7983 7501.0105 -3.895 0.000098856 ***
## dowSunday -1.0190 0.7902 7501.7729 -1.290 0.1973
## dowThursday 1.8249 0.7583 7500.9624 2.407 0.0161 *
## dowTuesday 3.7597 0.7500 7500.4863 5.013 0.000000547 ***
## dowWednesday 1.9569 0.7698 7499.0195 2.542 0.0110 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) lckdwn dwMndy dwStrd dwSndy dwThrs dwTsdy
## lockdown -0.133
## dowMonday -0.379 -0.029
## dowSaturday -0.359 -0.046 0.523
## dowSunday -0.371 0.004 0.527 0.503
## dowThursday -0.383 -0.016 0.550 0.526 0.529
## dowTuesday -0.397 0.046 0.554 0.528 0.535 0.558
## dowWednesdy -0.381 0.008 0.540 0.515 0.520 0.542 0.548PA ~ RE * Lockdown
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: PA_avg ~ roaming_entropy * lockdown + time_of_day + precipi +
## mean_temp + distance + dow + (1 | subject)
## Data: df
##
## REML criterion at convergence: 66802.9
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.7583 -0.5562 0.0505 0.6093 4.0440
##
## Random effects:
## Groups Name Variance Std.Dev.
## subject (Intercept) 122.9 11.09
## Residual 297.6 17.25
## Number of obs: 7753, groups: subject, 253
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 54.483369 1.899466 4733.185663 28.684 < 2e-16
## roaming_entropy 0.293447 0.292981 7619.289419 1.002 0.316573
## lockdown -6.831692 0.895424 7580.356521 -7.630 2.64e-14
## time_of_day 0.024595 0.011565 7529.445607 2.127 0.033480
## precipi -1.839107 0.969954 7513.400047 -1.896 0.057988
## mean_temp -0.012451 0.020965 7733.803832 -0.594 0.552583
## distance 0.002582 0.000706 7531.671010 3.657 0.000257
## dowMonday -2.440498 0.761113 7512.047215 -3.206 0.001349
## dowSaturday 3.417232 0.789697 7504.457338 4.327 1.53e-05
## dowSunday 0.358199 0.791788 7508.655234 0.452 0.650999
## dowThursday -2.609492 0.749655 7501.237973 -3.481 0.000503
## dowTuesday -4.668881 0.742889 7507.337599 -6.285 3.47e-10
## dowWednesday -2.655735 0.758212 7499.387445 -3.503 0.000463
## roaming_entropy:lockdown 1.158606 0.542039 7586.998947 2.137 0.032590
##
## (Intercept) ***
## roaming_entropy
## lockdown ***
## time_of_day *
## precipi .
## mean_temp
## distance ***
## dowMonday **
## dowSaturday ***
## dowSunday
## dowThursday ***
## dowTuesday ***
## dowWednesday ***
## roaming_entropy:lockdown *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## fit warnings:
## Some predictor variables are on very different scales: consider rescaling
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: PA_avg ~ roaming_entropy * lockdown + dow + (1 | subject)
## Data: df
##
## REML criterion at convergence: 66801.4
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.7564 -0.5571 0.0466 0.6022 4.0329
##
## Random effects:
## Groups Name Variance Std.Dev.
## subject (Intercept) 122.8 11.08
## Residual 298.4 17.27
## Number of obs: 7753, groups: subject, 253
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 53.8299 1.1557 1384.5528 46.576 < 2e-16 ***
## roaming_entropy 0.4920 0.2862 7616.6152 1.719 0.085574 .
## lockdown -6.7142 0.8877 7585.8766 -7.564 4.37e-14 ***
## dowMonday -2.3425 0.7510 7504.1796 -3.119 0.001821 **
## dowSaturday 3.4399 0.7895 7507.9983 4.357 1.34e-05 ***
## dowSunday 0.6676 0.7875 7509.7399 0.848 0.396639
## dowThursday -2.4522 0.7467 7505.8425 -3.284 0.001028 **
## dowTuesday -4.6676 0.7384 7504.4309 -6.321 2.74e-10 ***
## dowWednesday -2.5787 0.7580 7503.2646 -3.402 0.000673 ***
## roaming_entropy:lockdown 1.0385 0.5398 7590.3762 1.924 0.054410 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) rmng_n lckdwn dwMndy dwStrd dwSndy dwThrs dwTsdy dwWdns
## romng_ntrpy -0.616
## lockdown -0.513 0.736
## dowMonday -0.382 0.051 0.012
## dowSaturday -0.378 0.075 0.064 0.522
## dowSunday -0.435 0.157 0.115 0.528 0.506
## dowThursday -0.372 0.029 0.019 0.550 0.526 0.527
## dowTuesday -0.383 0.026 0.040 0.554 0.527 0.532 0.558
## dowWednesdy -0.369 0.027 0.017 0.541 0.514 0.518 0.542 0.548
## rmng_ntrpy: 0.306 -0.493 -0.781 -0.004 -0.091 -0.073 -0.024 -0.010 -0.001
PA ~ NL * Lockdown
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: PA_avg ~ novel_locations * lockdown + time_of_day + precipi +
## mean_temp + distance + dow + (1 | subject)
## Data: df
##
## REML criterion at convergence: 64753.8
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.8414 -0.5483 0.0553 0.6007 4.0800
##
## Random effects:
## Groups Name Variance Std.Dev.
## subject (Intercept) 121.2 11.01
## Residual 295.4 17.19
## Number of obs: 7519, groups: subject, 249
##
## Fixed effects:
## Estimate Std. Error df t value
## (Intercept) 52.9672016 1.8447225 4278.7362131 28.713
## novel_locations 0.0302826 0.0046105 7363.3261734 6.568
## lockdown -5.0629320 0.5503620 7390.5125056 -9.199
## time_of_day 0.0290147 0.0117003 7298.3556906 2.480
## precipi -1.9355484 0.9690284 7283.9255619 -1.997
## mean_temp -0.0061121 0.0210864 7493.5500071 -0.290
## distance 0.0009840 0.0007336 7311.8712455 1.341
## dowMonday -1.9176134 0.7792697 7282.6287622 -2.461
## dowSaturday 3.3282634 0.7965258 7272.6261081 4.178
## dowSunday 0.5668278 0.7936949 7276.5970184 0.714
## dowThursday -2.4404664 0.7630201 7269.3322930 -3.198
## dowTuesday -4.2246989 0.7584080 7278.5027727 -5.570
## dowWednesday -2.2226676 0.7791500 7268.4595329 -2.853
## novel_locations:lockdown -0.0082004 0.0109194 7352.5164368 -0.751
## Pr(>|t|)
## (Intercept) < 2e-16 ***
## novel_locations 5.44e-11 ***
## lockdown < 2e-16 ***
## time_of_day 0.01317 *
## precipi 0.04582 *
## mean_temp 0.77193
## distance 0.17983
## dowMonday 0.01389 *
## dowSaturday 2.97e-05 ***
## dowSunday 0.47515
## dowThursday 0.00139 **
## dowTuesday 2.63e-08 ***
## dowWednesday 0.00435 **
## novel_locations:lockdown 0.45268
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## fit warnings:
## Some predictor variables are on very different scales: consider rescaling
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: PA_avg ~ novel_locations * lockdown + dow + (1 | subject)
## Data: df
##
## REML criterion at convergence: 64742.3
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.8312 -0.5465 0.0516 0.6025 4.0690
##
## Random effects:
## Groups Name Variance Std.Dev.
## subject (Intercept) 121.1 11.0
## Residual 295.8 17.2
## Number of obs: 7519, groups: subject, 249
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 53.121772 0.959370 701.900166 55.372 < 2e-16
## novel_locations 0.032484 0.004335 7355.348669 7.493 7.53e-14
## lockdown -5.168858 0.531430 7381.405129 -9.726 < 2e-16
## dowMonday -1.844018 0.768544 7273.261230 -2.399 0.01645
## dowSaturday 3.276834 0.796362 7276.432394 4.115 3.92e-05
## dowSunday 0.721322 0.788821 7275.113761 0.914 0.36052
## dowThursday -2.254667 0.759206 7273.647964 -2.970 0.00299
## dowTuesday -4.206796 0.753528 7274.389071 -5.583 2.45e-08
## dowWednesday -2.123642 0.778285 7272.194384 -2.729 0.00638
## novel_locations:lockdown -0.009292 0.010882 7356.806450 -0.854 0.39323
##
## (Intercept) ***
## novel_locations ***
## lockdown ***
## dowMonday *
## dowSaturday ***
## dowSunday
## dowThursday **
## dowTuesday ***
## dowWednesday **
## novel_locations:lockdown
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) nvl_lc lckdwn dwMndy dwStrd dwSndy dwThrs dwTsdy dwWdns
## novel_lctns -0.287
## lockdown -0.260 0.454
## dowMonday -0.452 0.065 0.000
## dowSaturday -0.414 -0.015 -0.005 0.526
## dowSunday -0.442 0.044 0.028 0.535 0.513
## dowThursday -0.458 0.053 0.023 0.558 0.536 0.541
## dowTuesday -0.484 0.092 0.083 0.562 0.535 0.548 0.569
## dowWednesdy -0.448 0.050 0.025 0.542 0.519 0.527 0.548 0.553
## nvl_lctns:l 0.111 -0.366 -0.528 -0.006 -0.065 -0.011 -0.034 -0.030 -0.008
PA ~ Distance * Lockdown Varying Distances
PA ~ RE * Pre_COVID_RE Post-Lockdown
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: PA_avg ~ roaming_entropy * pre_covid_re + time_of_day + precipi +
## mean_temp + distance + dow + (1 | subject)
## Data: df[which(df$lockdown == 1), ]
##
## REML criterion at convergence: 25069
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.5388 -0.5607 0.0590 0.5732 4.1536
##
## Random effects:
## Groups Name Variance Std.Dev.
## subject (Intercept) 171.8 13.11
## Residual 264.4 16.26
## Number of obs: 2925, groups: subject, 214
##
## Fixed effects:
## Estimate Std. Error df t value
## (Intercept) 38.5265443 7.5158710 353.5894068 5.126
## roaming_entropy -1.4271372 3.3708954 2889.6241913 -0.423
## pre_covid_re 1.6274171 2.7789674 270.6408637 0.586
## time_of_day -0.0008738 0.0183000 2762.4672944 -0.048
## precipi -4.0172055 1.1507238 2748.3055933 -3.491
## mean_temp 0.0539711 0.0446240 1083.2010358 1.209
## distance -0.0038979 0.0073188 2754.8888409 -0.533
## dowMonday -1.2661458 1.1394276 2730.3003359 -1.111
## dowSaturday 2.8923753 1.2052134 2744.8103719 2.400
## dowSunday 2.7646728 1.2293023 2732.4084599 2.249
## dowThursday -0.6215076 1.1436025 2725.8309514 -0.543
## dowTuesday 1.0467584 1.2354475 2726.0394667 0.847
## dowWednesday 0.8644845 1.2035310 2738.1766210 0.718
## roaming_entropy:pre_covid_re 1.5800457 1.3844358 2892.5158928 1.141
## Pr(>|t|)
## (Intercept) 0.000000488 ***
## roaming_entropy 0.672057
## pre_covid_re 0.558619
## time_of_day 0.961920
## precipi 0.000489 ***
## mean_temp 0.226748
## distance 0.594355
## dowMonday 0.266575
## dowSaturday 0.016466 *
## dowSunday 0.024593 *
## dowThursday 0.586854
## dowTuesday 0.396919
## dowWednesday 0.472640
## roaming_entropy:pre_covid_re 0.253843
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: PA_avg ~ roaming_entropy * pre_covid_re + +dow + (1 | subject)
## Data: df[which(df$lockdown == 1), ]
##
## REML criterion at convergence: 25066.4
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.5265 -0.5443 0.0641 0.5712 3.9461
##
## Random effects:
## Groups Name Variance Std.Dev.
## subject (Intercept) 172.5 13.13
## Residual 265.3 16.29
## Number of obs: 2925, groups: subject, 214
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 42.3251 6.5694 268.3979 6.443 5.4e-10
## roaming_entropy -1.0799 3.3734 2893.2604 -0.320 0.7489
## pre_covid_re 1.3736 2.7647 266.6498 0.497 0.6197
## dowMonday -1.6153 1.1361 2731.9017 -1.422 0.1552
## dowSaturday 1.8874 1.1761 2739.7806 1.605 0.1086
## dowSunday 2.3385 1.2218 2729.2842 1.914 0.0557
## dowThursday -0.6211 1.1455 2729.0918 -0.542 0.5877
## dowTuesday 0.4907 1.2233 2724.4238 0.401 0.6883
## dowWednesday 0.4830 1.1971 2733.9484 0.403 0.6866
## roaming_entropy:pre_covid_re 1.4176 1.3831 2895.2946 1.025 0.3055
##
## (Intercept) ***
## roaming_entropy
## pre_covid_re
## dowMonday
## dowSaturday
## dowSunday .
## dowThursday
## dowTuesday
## dowWednesday
## roaming_entropy:pre_covid_re
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) rmng_n pr_cv_ dwMndy dwStrd dwSndy dwThrs dwTsdy dwWdns
## romng_ntrpy -0.333
## pre_covid_r -0.979 0.332
## dowMonday -0.097 -0.012 -0.006
## dowSaturday -0.099 -0.013 0.008 0.558
## dowSunday -0.086 -0.025 -0.008 0.540 0.521
## dowThursday -0.096 -0.020 -0.001 0.574 0.559 0.535
## dowTuesday -0.079 -0.037 -0.014 0.537 0.518 0.499 0.534
## dowWednesdy -0.090 -0.018 -0.007 0.556 0.530 0.511 0.545 0.511
## rmng_ntr:__ 0.340 -0.989 -0.349 0.016 -0.003 0.025 0.016 0.037 0.022
PA ~ NL * Pre_COVID_RE Post-Lockdown
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: PA_avg ~ novel_locations * pre_covid_re + time_of_day + precipi +
## mean_temp + distance + dow + (1 | subject)
## Data: df[which(df$lockdown == 1), ]
##
## REML criterion at convergence: 25093.3
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.4882 -0.5539 0.0567 0.5683 4.1140
##
## Random effects:
## Groups Name Variance Std.Dev.
## subject (Intercept) 170.7 13.06
## Residual 265.5 16.29
## Number of obs: 2925, groups: subject, 214
##
## Fixed effects:
## Estimate Std. Error df t value
## (Intercept) 35.929242 7.216043 309.360741 4.979
## novel_locations 0.067198 0.093797 2877.426871 0.716
## pre_covid_re 3.278750 2.628208 222.476453 1.248
## time_of_day -0.002540 0.018328 2762.944594 -0.139
## precipi -4.080380 1.152132 2748.543292 -3.542
## mean_temp 0.055915 0.044632 1073.811082 1.253
## distance -0.004469 0.007820 2739.575791 -0.571
## dowMonday -1.343857 1.141654 2730.649062 -1.177
## dowSaturday 2.990836 1.207676 2743.047227 2.477
## dowSunday 2.773956 1.231268 2732.240469 2.253
## dowThursday -0.615422 1.145936 2725.449059 -0.537
## dowTuesday 1.073488 1.236837 2725.613992 0.868
## dowWednesday 0.783433 1.205776 2738.184672 0.650
## novel_locations:pre_covid_re -0.010752 0.037368 2877.780966 -0.288
## Pr(>|t|)
## (Intercept) 0.00000106 ***
## novel_locations 0.473789
## pre_covid_re 0.213517
## time_of_day 0.889795
## precipi 0.000404 ***
## mean_temp 0.210545
## distance 0.567773
## dowMonday 0.239253
## dowSaturday 0.013327 *
## dowSunday 0.024343 *
## dowThursday 0.591279
## dowTuesday 0.385509
## dowWednesday 0.515919
## novel_locations:pre_covid_re 0.773574
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: PA_avg ~ novel_locations * pre_covid_re + dow + (1 | subject)
## Data: df[which(df$lockdown == 1), ]
##
## REML criterion at convergence: 25091.3
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.4989 -0.5431 0.0569 0.5651 4.0133
##
## Random effects:
## Groups Name Variance Std.Dev.
## subject (Intercept) 171.4 13.09
## Residual 266.4 16.32
## Number of obs: 2925, groups: subject, 214
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 40.06134 6.24787 224.66766 6.412 8.37e-10
## novel_locations 0.06353 0.09338 2882.03755 0.680 0.4964
## pre_covid_re 2.91498 2.61625 219.08055 1.114 0.2664
## dowMonday -1.69589 1.13848 2732.19586 -1.490 0.1364
## dowSaturday 1.98747 1.17980 2737.46142 1.685 0.0922
## dowSunday 2.34314 1.22398 2729.10123 1.914 0.0557
## dowThursday -0.60792 1.14790 2728.63046 -0.530 0.5964
## dowTuesday 0.51327 1.22500 2723.99297 0.419 0.6753
## dowWednesday 0.39873 1.19955 2734.08959 0.332 0.7396
## novel_locations:pre_covid_re -0.01038 0.03739 2881.69984 -0.278 0.7814
##
## (Intercept) ***
## novel_locations
## pre_covid_re
## dowMonday
## dowSaturday .
## dowSunday .
## dowThursday
## dowTuesday
## dowWednesday
## novel_locations:pre_covid_re
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) nvl_lc pr_cv_ dwMndy dwStrd dwSndy dwThrs dwTsdy dwWdns
## novel_lctns -0.156
## pre_covid_r -0.979 0.156
## dowMonday -0.103 -0.021 -0.004
## dowSaturday -0.104 -0.025 0.005 0.558
## dowSunday -0.097 -0.010 -0.001 0.540 0.520
## dowThursday -0.104 -0.025 0.000 0.575 0.559 0.534
## dowTuesday -0.096 0.002 -0.003 0.537 0.516 0.498 0.533
## dowWednesdy -0.099 -0.022 -0.003 0.556 0.530 0.512 0.545 0.510
## nvl_lctn:__ 0.161 -0.994 -0.166 0.024 0.012 0.011 0.022 -0.001 0.025
```