RE_COVID_Initial_OBS
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: 40550
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.9351 -0.5317 0.0479 0.6135 3.4051
##
## Random effects:
## Groups Name Variance Std.Dev.
## subject (Intercept) 100.4 10.02
## Residual 293.2 17.12
## Number of obs: 4704, groups: subject, 235
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 63.7195767 2.6286060 4561.2296398 24.241 < 2e-16 ***
## roaming_entropy 0.6839690 0.3054312 4633.6432294 2.239 0.02518 *
## time_of_day 0.0393902 0.0147668 4513.8747764 2.667 0.00767 **
## precipi 1.9529342 1.7794152 4510.3729154 1.098 0.27248
## mean_temp -0.1454717 0.0313951 4592.1580271 -4.634 0.000003693 ***
## distance 0.0020185 0.0007145 4524.1150356 2.825 0.00475 **
## dowMonday -3.3458946 1.0370986 4485.3240767 -3.226 0.00126 **
## dowSaturday 5.1926165 1.0515998 4487.1482281 4.938 0.000000819 ***
## dowSunday -0.7705915 1.0374267 4490.4821343 -0.743 0.45765
## dowThursday -3.6902263 0.9808393 4480.1967554 -3.762 0.00017 ***
## dowTuesday -7.9830591 0.9396690 4484.5468147 -8.496 < 2e-16 ***
## dowWednesday -4.2435757 0.9833081 4477.6926955 -4.316 0.000016260 ***
## ---
## 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 -0.246
## time_of_day -0.165 0.018
## precipi -0.084 0.039 0.023
## mean_temp -0.857 -0.065 -0.008 -0.050
## distance -0.030 -0.225 0.006 -0.013 0.088
## dowMonday -0.463 0.054 0.030 0.204 0.270 0.025
## dowSaturday -0.171 0.117 -0.006 0.157 -0.067 -0.047 0.474
## dowSunday -0.409 0.207 -0.007 0.165 0.171 -0.086 0.553 0.491
## dowThursday -0.259 0.041 -0.001 0.220 0.035 0.003 0.544 0.515 0.535
## dowTuesday -0.411 0.026 -0.009 0.098 0.221 0.022 0.590 0.505 0.568
## dowWednesdy -0.280 0.042 0.002 0.223 0.059 0.002 0.549 0.511 0.538
## dwThrs dwTsdy
## romng_ntrpy
## time_of_day
## precipi
## mean_temp
## distance
## dowMonday
## dowSaturday
## dowSunday
## dowThursday
## dowTuesday 0.568
## dowWednesdy 0.562 0.569
## 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: 40568
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -4.0355 -0.5295 0.0446 0.6067 3.3217
##
## Random effects:
## Groups Name Variance Std.Dev.
## subject (Intercept) 100.7 10.04
## Residual 295.5 17.19
## Number of obs: 4704, groups: subject, 235
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 54.3502 1.2338 1715.3175 44.052 < 2e-16 ***
## roaming_entropy 0.7866 0.2982 4634.3583 2.638 0.008375 **
## dowMonday -2.3267 0.9760 4481.2255 -2.384 0.017165 *
## dowSaturday 4.8901 1.0397 4488.6743 4.703 2.64e-06 ***
## dowSunday 0.2551 1.0046 4489.7848 0.254 0.799589
## dowThursday -3.7095 0.9594 4483.6438 -3.866 0.000112 ***
## dowTuesday -7.0987 0.9143 4482.4842 -7.764 1.01e-14 ***
## dowWednesday -4.1609 0.9599 4479.6515 -4.335 1.49e-05 ***
## ---
## 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 -0.624
## dowMonday -0.455 0.070
## dowSaturday -0.452 0.103 0.497
## dowSunday -0.526 0.203 0.519 0.496
## dowThursday -0.442 0.038 0.533 0.503 0.522
## dowTuesday -0.464 0.039 0.558 0.527 0.547 0.568
## dowWednesdy -0.443 0.039 0.531 0.501 0.521 0.538 0.564PA ~ 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: 38633.6
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.8907 -0.5282 0.0526 0.6214 3.4599
##
## Random effects:
## Groups Name Variance Std.Dev.
## subject (Intercept) 98.33 9.916
## Residual 289.66 17.019
## Number of obs: 4486, groups: subject, 235
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 62.1259866 2.6129661 4355.0657506 23.776 < 2e-16 ***
## novel_locations 0.0284147 0.0047158 4386.3531176 6.025 1.83e-09 ***
## time_of_day 0.0471188 0.0150448 4299.5662055 3.132 0.001749 **
## precipi 1.9126912 1.7893848 4296.3350614 1.069 0.285170
## mean_temp -0.1271263 0.0315680 4381.5294856 -4.027 5.74e-05 ***
## distance 0.0007613 0.0007388 4320.9160757 1.030 0.302886
## dowMonday -2.3215189 1.0807146 4270.2537863 -2.148 0.031759 *
## dowSaturday 4.7977942 1.0656279 4266.1914477 4.502 6.90e-06 ***
## dowSunday -0.6807521 1.0444545 4268.6132021 -0.652 0.514580
## dowThursday -3.3934806 1.0116515 4264.8165389 -3.354 0.000802 ***
## dowTuesday -7.3296071 0.9725761 4272.7288483 -7.536 5.87e-14 ***
## dowWednesday -3.6636573 1.0287113 4262.9821406 -3.561 0.000373 ***
## ---
## 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 -0.201
## time_of_day -0.167 0.001
## precipi -0.086 0.024 0.022
## mean_temp -0.895 0.090 -0.004 -0.048
## distance -0.015 -0.340 0.009 -0.011 0.040
## dowMonday -0.475 0.112 0.035 0.214 0.270 -0.005
## dowSaturday -0.150 -0.018 -0.009 0.172 -0.066 -0.013 0.482
## dowSunday -0.393 0.101 -0.012 0.183 0.187 -0.072 0.569 0.498
## dowThursday -0.270 0.080 -0.002 0.236 0.034 -0.015 0.556 0.532 0.561
## dowTuesday -0.434 0.137 -0.007 0.118 0.218 -0.020 0.604 0.520 0.598
## dowWednesdy -0.295 0.082 0.000 0.232 0.066 -0.019 0.555 0.520 0.557
## dwThrs dwTsdy
## novel_lctns
## time_of_day
## precipi
## mean_temp
## distance
## dowMonday
## dowSaturday
## dowSunday
## dowThursday
## dowTuesday 0.589
## dowWednesdy 0.573 0.581
## 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: 38640.2
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.9500 -0.5263 0.0482 0.6166 3.3909
##
## Random effects:
## Groups Name Variance Std.Dev.
## subject (Intercept) 98.61 9.93
## Residual 291.24 17.07
## Number of obs: 4486, groups: subject, 235
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 54.306475 1.027725 999.906489 52.841 < 2e-16 ***
## novel_locations 0.031892 0.004418 4375.545796 7.219 6.16e-13 ***
## dowMonday -1.445749 1.013175 4263.587007 -1.427 0.153668
## dowSaturday 4.408646 1.050596 4268.202205 4.196 2.77e-05 ***
## dowSunday 0.075401 1.005631 4265.592852 0.075 0.940235
## dowThursday -3.423930 0.984557 4267.245919 -3.478 0.000511 ***
## dowTuesday -6.528255 0.943055 4268.091839 -6.922 5.10e-12 ***
## dowWednesday -3.563482 0.999880 4264.009131 -3.564 0.000369 ***
## ---
## 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 -0.298
## dowMonday -0.539 0.088
## dowSaturday -0.491 -0.021 0.502
## dowSunday -0.536 0.058 0.528 0.506
## dowThursday -0.551 0.072 0.544 0.517 0.544
## dowTuesday -0.588 0.116 0.570 0.539 0.571 0.586
## dowWednesdy -0.540 0.069 0.533 0.508 0.534 0.547 0.572RE ~ 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: 18289.9
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -4.8045 -0.6161 0.0784 0.6475 5.1130
##
## Random effects:
## Groups Name Variance Std.Dev.
## subject (Intercept) 0.08609 0.2934
## Residual 0.61030 0.7812
## Number of obs: 7600, groups: subject, 235
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 2.23332494 0.07637353 5203.81162561 29.242 < 2e-16 ***
## lockdown -1.37826352 0.02024977 7555.64423459 -68.063 < 2e-16 ***
## time_of_day -0.00086690 0.00052751 7433.35657459 -1.643 0.10035
## precipi -0.04195687 0.04408735 7412.04692778 -0.952 0.34129
## mean_temp 0.00336143 0.00092922 6822.53759508 3.617 0.00030 ***
## distance 0.00054220 0.00003119 7446.07458771 17.382 < 2e-16 ***
## dowMonday -0.15534584 0.03471771 7407.60561552 -4.475 0.00000777 ***
## dowSaturday -0.11232246 0.03582602 7386.67966176 -3.135 0.00172 **
## dowSunday -0.45042623 0.03566455 7389.61321366 -12.630 < 2e-16 ***
## dowThursday -0.05495296 0.03420568 7382.98487046 -1.607 0.10820
## dowTuesday -0.04916465 0.03393596 7393.23307331 -1.449 0.14745
## dowWednesday -0.09611265 0.03464714 7378.91899491 -2.774 0.00555 **
## ---
## 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 -0.291
## time_of_day -0.208 0.005
## precipi -0.018 -0.200 0.022
## mean_temp -0.879 0.244 0.003 -0.048
## distance -0.067 0.113 0.009 0.000 0.039
## dowMonday -0.383 0.000 0.034 0.053 0.153 0.019
## dowSaturday -0.228 -0.037 -0.002 -0.043 0.003 -0.018 0.513
## dowSunday -0.315 0.018 -0.011 0.015 0.095 -0.041 0.530 0.500
## dowThursday -0.264 -0.030 -0.003 0.100 0.018 0.007 0.548 0.519 0.527
## dowTuesday -0.350 0.076 -0.003 -0.031 0.116 0.016 0.557 0.525 0.537
## dowWednesdy -0.271 0.006 0.001 0.047 0.030 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 0.544
## 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: 50657.6
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.8257 -0.6328 0.0263 0.6198 8.3853
##
## Random effects:
## Groups Name Variance Std.Dev.
## subject (Intercept) 0.1144 0.3382
## Residual 0.6973 0.8351
## Number of obs: 20179, groups: subject, 236
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 2.50502 0.02751 484.85536 91.046 < 2e-16 ***
## lockdown -1.27637 0.01223 20140.08462 -104.364 < 2e-16 ***
## dowMonday -0.18130 0.02205 19944.67274 -8.222 < 2e-16 ***
## dowSaturday -0.18098 0.02236 19944.74709 -8.093 6.14e-16 ***
## dowSunday -0.41082 0.02220 19946.22733 -18.502 < 2e-16 ***
## dowThursday -0.06820 0.02172 19943.51170 -3.140 0.00169 **
## dowTuesday -0.15661 0.02176 19944.87451 -7.198 6.35e-13 ***
## dowWednesday -0.12033 0.02180 19943.46055 -5.520 3.44e-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 -0.181
## dowMonday -0.394 -0.007
## dowSaturday -0.386 -0.024 0.487
## dowSunday -0.395 0.006 0.491 0.484
## dowThursday -0.399 -0.011 0.501 0.495 0.498
## dowTuesday -0.401 0.000 0.501 0.493 0.497 0.508
## dowWednesdy -0.401 0.005 0.500 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: 78122.1
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -8.5540 -0.5112 -0.1836 0.2604 13.2159
##
## Random effects:
## Groups Name Variance Std.Dev.
## subject (Intercept) 196 14.00
## Residual 2222 47.14
## Number of obs: 7382, groups: subject, 235
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 79.46594920 4.52258822 4680.14234864 17.571 < 2e-16 ***
## lockdown -34.01416743 1.22752270 7367.45084975 -27.710 < 2e-16 ***
## time_of_day -0.00002221 0.03226673 7240.86793319 -0.001 0.99945
## precipi -2.32062583 2.66456683 7215.83312960 -0.871 0.38383
## mean_temp -0.27670139 0.05542853 5473.36047005 -4.992 6.16e-07 ***
## distance 0.05593241 0.00188585 7261.30932870 29.659 < 2e-16 ***
## dowMonday -14.11917046 2.14502091 7202.55129276 -6.582 4.96e-11 ***
## dowSaturday 7.07487999 2.19149956 7175.91165405 3.228 0.00125 **
## dowSunday -12.14535664 2.18625649 7181.69262052 -5.555 2.87e-08 ***
## dowThursday -8.38355531 2.10313960 7173.92850023 -3.986 6.78e-05 ***
## dowTuesday -16.91209404 2.08512427 7184.91787399 -8.111 5.87e-16 ***
## dowWednesday -10.35630317 2.15075756 7169.52112856 -4.815 1.50e-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 -0.296
## time_of_day -0.215 0.003
## precipi -0.021 -0.195 0.022
## mean_temp -0.882 0.241 0.003 -0.049
## distance -0.070 0.115 0.008 0.001 0.040
## dowMonday -0.387 -0.003 0.037 0.055 0.142 0.017
## dowSaturday -0.240 -0.029 -0.002 -0.038 -0.001 -0.017 0.521
## dowSunday -0.324 0.024 -0.013 0.020 0.088 -0.040 0.536 0.512
## dowThursday -0.273 -0.025 -0.003 0.103 0.011 0.007 0.553 0.530 0.538
## dowTuesday -0.357 0.080 -0.001 -0.026 0.105 0.016 0.561 0.536 0.547
## dowWednesdy -0.280 0.004 0.000 0.047 0.027 0.006 0.539 0.519 0.525
## dwThrs dwTsdy
## lockdown
## time_of_day
## precipi
## mean_temp
## distance
## dowMonday
## dowSaturday
## dowSunday
## dowThursday
## dowTuesday 0.559
## dowWednesdy 0.548 0.549
## 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: 201341.8
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -2.0560 -0.5151 -0.2065 0.2194 18.1264
##
## Random effects:
## Groups Name Variance Std.Dev.
## subject (Intercept) 287.2 16.95
## Residual 2878.1 53.65
## Number of obs: 18594, groups: subject, 236
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 65.4615 1.5660 702.9386 41.802 < 2e-16 ***
## lockdown -29.9202 0.8134 18586.0000 -36.783 < 2e-16 ***
## dowMonday -15.9583 1.4763 18360.9852 -10.810 < 2e-16 ***
## dowSaturday 3.0628 1.4973 18362.4381 2.046 0.0408 *
## dowSunday -8.3229 1.4870 18363.3419 -5.597 0.0000000221 ***
## dowThursday -7.5872 1.4519 18359.8449 -5.226 0.0000001753 ***
## dowTuesday -13.5934 1.4553 18361.3992 -9.341 < 2e-16 ***
## dowWednesday -12.2980 1.4581 18359.8400 -8.434 < 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 -0.231
## dowMonday -0.462 -0.008
## dowSaturday -0.451 -0.027 0.486
## dowSunday -0.463 0.006 0.489 0.483
## dowThursday -0.469 -0.012 0.501 0.494 0.497
## dowTuesday -0.471 0.000 0.500 0.493 0.497 0.509
## dowWednesdy -0.471 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: 65436.2
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.7609 -0.5503 0.0519 0.6008 4.0604
##
## Random effects:
## Groups Name Variance Std.Dev.
## subject (Intercept) 110.9 10.53
## Residual 297.0 17.23
## Number of obs: 7600, groups: subject, 235
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 55.9905095 1.8028034 4180.6145814 31.057 < 2e-16 ***
## lockdown -6.1381870 0.4492333 7470.8456718 -13.664 < 2e-16 ***
## time_of_day 0.0231544 0.0116553 7394.2893472 1.987 0.047005 *
## precipi -2.0138002 0.9736188 7383.5972288 -2.068 0.038640 *
## mean_temp -0.0151195 0.0210268 7571.2815933 -0.719 0.472126
## distance 0.0027475 0.0006894 7400.0173462 3.985 6.81e-05 ***
## dowMonday -2.5588679 0.7666255 7381.4490484 -3.338 0.000849 ***
## dowSaturday 3.4074295 0.7907371 7371.5958353 4.309 1.66e-05 ***
## dowSunday 0.3890657 0.7872355 7373.9914289 0.494 0.621167
## dowThursday -2.7613043 0.7549105 7369.6332947 -3.658 0.000256 ***
## dowTuesday -4.7998337 0.7491348 7375.3764413 -6.407 1.57e-10 ***
## dowWednesday -2.7413840 0.7645870 7367.6839030 -3.585 0.000339 ***
## ---
## 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 -0.278
## time_of_day -0.196 0.005
## precipi -0.016 -0.200 0.021
## mean_temp -0.843 0.246 0.004 -0.049
## distance -0.062 0.112 0.009 0.000 0.037
## dowMonday -0.364 0.001 0.034 0.053 0.157 0.019
## dowSaturday -0.213 -0.037 -0.002 -0.043 0.002 -0.018 0.512
## dowSunday -0.299 0.019 -0.011 0.015 0.097 -0.041 0.530 0.500
## dowThursday -0.247 -0.030 -0.003 0.100 0.018 0.007 0.548 0.519 0.527
## dowTuesday -0.332 0.076 -0.003 -0.031 0.119 0.016 0.557 0.525 0.538
## dowWednesdy -0.254 0.006 0.001 0.047 0.030 0.008 0.538 0.512 0.519
## dwThrs dwTsdy
## lockdown
## time_of_day
## precipi
## mean_temp
## distance
## dowMonday
## dowSaturday
## dowSunday
## dowThursday
## dowTuesday 0.549
## dowWednesdy 0.543 0.544
## 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: 65437.3
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.7724 -0.5517 0.0488 0.6037 4.0525
##
## Random effects:
## Groups Name Variance Std.Dev.
## subject (Intercept) 110.8 10.53
## Residual 297.8 17.26
## Number of obs: 7600, groups: subject, 235
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 55.5937 0.9008 572.5513 61.714 < 2e-16 ***
## lockdown -6.4301 0.4252 7467.5013 -15.122 < 2e-16 ***
## dowMonday -2.4634 0.7563 7372.3290 -3.257 0.001131 **
## dowSaturday 3.3955 0.7910 7375.3794 4.293 1.79e-05 ***
## dowSunday 0.6359 0.7837 7373.4125 0.811 0.417156
## dowThursday -2.6031 0.7520 7374.1421 -3.462 0.000540 ***
## dowTuesday -4.8061 0.7446 7371.9998 -6.454 1.16e-10 ***
## dowWednesday -2.6695 0.7644 7371.4363 -3.492 0.000482 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) lckdwn dwMndy dwStrd dwSndy dwThrs dwTsdy
## lockdown -0.163
## dowMonday -0.452 -0.029
## dowSaturday -0.430 -0.047 0.523
## dowSunday -0.442 0.003 0.526 0.504
## dowThursday -0.457 -0.017 0.550 0.527 0.529
## dowTuesday -0.473 0.044 0.552 0.528 0.534 0.557
## dowWednesdy -0.454 0.007 0.539 0.515 0.520 0.542 0.546NA ~ 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: 65832.3
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.5769 -0.6260 -0.0655 0.5539 4.4677
##
## Random effects:
## Groups Name Variance Std.Dev.
## subject (Intercept) 189.5 13.77
## Residual 308.4 17.56
## Number of obs: 7600, groups: subject, 235
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 39.799952 1.931040 2976.320611 20.611 < 2e-16 ***
## lockdown 3.756539 0.458610 7432.765633 8.191 3.02e-16 ***
## time_of_day -0.021944 0.011884 7379.268544 -1.846 0.064863 .
## precipi 2.041987 0.992609 7371.987982 2.057 0.039703 *
## mean_temp 0.012518 0.021585 7578.371525 0.580 0.561971
## distance -0.002198 0.000703 7382.747374 -3.126 0.001779 **
## dowMonday 1.244207 0.781555 7370.481514 1.592 0.111436
## dowSaturday -3.049588 0.806030 7364.062095 -3.783 0.000156 ***
## dowSunday -0.959183 0.802491 7366.407078 -1.195 0.232025
## dowThursday 2.076830 0.769490 7362.728700 2.699 0.006971 **
## dowTuesday 3.811251 0.763665 7367.057950 4.991 6.15e-07 ***
## dowWednesday 2.004373 0.779333 7361.440017 2.572 0.010133 *
## ---
## 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 -0.266
## time_of_day -0.187 0.006
## precipi -0.014 -0.200 0.021
## mean_temp -0.808 0.246 0.004 -0.049
## distance -0.059 0.112 0.009 0.000 0.037
## dowMonday -0.349 0.002 0.034 0.053 0.158 0.019
## dowSaturday -0.203 -0.037 -0.003 -0.043 0.002 -0.018 0.512
## dowSunday -0.285 0.019 -0.011 0.014 0.098 -0.041 0.530 0.500
## dowThursday -0.235 -0.030 -0.003 0.100 0.017 0.007 0.547 0.519 0.527
## dowTuesday -0.318 0.076 -0.003 -0.031 0.119 0.016 0.557 0.525 0.538
## dowWednesdy -0.242 0.006 0.002 0.047 0.030 0.008 0.538 0.512 0.519
## dwThrs dwTsdy
## lockdown
## time_of_day
## precipi
## mean_temp
## distance
## dowMonday
## dowSaturday
## dowSunday
## dowThursday
## dowTuesday 0.549
## dowWednesdy 0.543 0.544
## 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: 65826.7
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.5657 -0.6293 -0.0675 0.5549 4.4978
##
## Random effects:
## Groups Name Variance Std.Dev.
## subject (Intercept) 189.5 13.77
## Residual 309.0 17.58
## Number of obs: 7600, groups: subject, 235
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 40.0884 1.0773 427.9039 37.212 < 2e-16 ***
## lockdown 4.0272 0.4338 7431.5681 9.283 < 2e-16 ***
## dowMonday 1.1522 0.7706 7365.9142 1.495 0.134872
## dowSaturday -3.0252 0.8059 7367.9580 -3.754 0.000176 ***
## dowSunday -1.1673 0.7984 7367.4570 -1.462 0.143765
## dowThursday 1.9151 0.7662 7367.1088 2.500 0.012453 *
## dowTuesday 3.8223 0.7586 7366.2917 5.038 0.00000048 ***
## dowWednesday 1.9303 0.7788 7365.3224 2.478 0.013216 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) lckdwn dwMndy dwStrd dwSndy dwThrs dwTsdy
## lockdown -0.138
## dowMonday -0.385 -0.029
## dowSaturday -0.366 -0.047 0.523
## dowSunday -0.377 0.003 0.526 0.504
## dowThursday -0.389 -0.017 0.550 0.527 0.529
## dowTuesday -0.403 0.043 0.552 0.528 0.534 0.557
## dowWednesdy -0.386 0.007 0.539 0.515 0.520 0.542 0.546PA ~ 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: 65427.1
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.7640 -0.5468 0.0491 0.6066 4.0451
##
## Random effects:
## Groups Name Variance Std.Dev.
## subject (Intercept) 110.8 10.53
## Residual 296.7 17.22
## Number of obs: 7600, groups: subject, 235
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 55.113748 1.905466 4711.890214 28.924 < 2e-16
## roaming_entropy 0.344825 0.295085 7475.902634 1.169 0.242617
## lockdown -6.581151 0.900484 7437.658312 -7.308 2.98e-13
## time_of_day 0.023681 0.011652 7392.593937 2.032 0.042151
## precipi -1.976503 0.973223 7381.775781 -2.031 0.042303
## mean_temp -0.014823 0.021089 7567.510146 -0.703 0.482154
## distance 0.002519 0.000705 7399.917407 3.573 0.000356
## dowMonday -2.457536 0.767235 7378.517055 -3.203 0.001365
## dowSaturday 3.337124 0.794463 7370.591371 4.200 2.69e-05
## dowSunday 0.560037 0.797195 7372.879285 0.703 0.482383
## dowThursday -2.759027 0.754852 7367.696588 -3.655 0.000259
## dowTuesday -4.771836 0.748864 7373.219110 -6.372 1.98e-10
## dowWednesday -2.680733 0.764596 7365.619103 -3.506 0.000457
## roaming_entropy:lockdown 1.010589 0.543723 7451.425647 1.859 0.063116
##
## (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: 65425.3
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.7693 -0.5504 0.0474 0.6013 4.0351
##
## Random effects:
## Groups Name Variance Std.Dev.
## subject (Intercept) 110.7 10.52
## Residual 297.4 17.25
## Number of obs: 7600, groups: subject, 235
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 54.2537 1.1518 1411.3111 47.104 < 2e-16 ***
## roaming_entropy 0.5401 0.2882 7472.8998 1.874 0.060967 .
## lockdown -6.4722 0.8927 7443.0408 -7.250 4.57e-13 ***
## dowMonday -2.3332 0.7571 7370.5069 -3.082 0.002067 **
## dowSaturday 3.3544 0.7943 7374.2579 4.223 2.44e-05 ***
## dowSunday 0.8779 0.7928 7374.3067 1.107 0.268153
## dowThursday -2.5887 0.7518 7372.2309 -3.443 0.000578 ***
## dowTuesday -4.7624 0.7444 7370.1866 -6.398 1.67e-10 ***
## dowWednesday -2.5919 0.7643 7369.5042 -3.391 0.000700 ***
## roaming_entropy:lockdown 0.8967 0.5415 7455.0963 1.656 0.097725 .
## ---
## 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 -0.624
## lockdown -0.521 0.737
## dowMonday -0.387 0.054 0.014
## dowSaturday -0.381 0.074 0.063 0.522
## dowSunday -0.439 0.155 0.114 0.527 0.506
## dowThursday -0.375 0.029 0.019 0.550 0.527 0.527
## dowTuesday -0.385 0.025 0.037 0.553 0.527 0.532 0.557
## dowWednesdy -0.373 0.029 0.018 0.540 0.514 0.518 0.542 0.547
## rmng_ntrpy: 0.310 -0.495 -0.782 -0.006 -0.092 -0.073 -0.024 -0.009 -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: 63512.3
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.8456 -0.5445 0.0543 0.5998 4.0830
##
## Random effects:
## Groups Name Variance Std.Dev.
## subject (Intercept) 109.8 10.48
## Residual 294.1 17.15
## Number of obs: 7382, groups: subject, 235
##
## Fixed effects:
## Estimate Std. Error df t value
## (Intercept) 53.7938933 1.8477370 4273.3864931 29.113
## novel_locations 0.0299498 0.0046173 7238.9349622 6.486
## lockdown -5.0041254 0.5515195 7264.3485676 -9.073
## time_of_day 0.0280818 0.0117760 7175.8243956 2.385
## precipi -2.0477633 0.9716943 7165.9445552 -2.107
## mean_temp -0.0096146 0.0211971 7340.9413595 -0.454
## distance 0.0009667 0.0007321 7194.4897010 1.320
## dowMonday -1.9081440 0.7842486 7162.4092946 -2.433
## dowSaturday 3.2569388 0.8005379 7152.7172526 4.068
## dowSunday 0.7388585 0.7982585 7156.2229377 0.926
## dowThursday -2.5594679 0.7672675 7150.7762233 -3.336
## dowTuesday -4.3376172 0.7634539 7157.6232827 -5.682
## dowWednesday -2.2248313 0.7844999 7149.8002894 -2.836
## novel_locations:lockdown -0.0091230 0.0109087 7234.6439988 -0.836
## Pr(>|t|)
## (Intercept) < 2e-16 ***
## novel_locations 9.37e-11 ***
## lockdown < 2e-16 ***
## time_of_day 0.017120 *
## precipi 0.035116 *
## mean_temp 0.650143
## distance 0.186719
## dowMonday 0.014995 *
## dowSaturday 4.78e-05 ***
## dowSunday 0.354691
## dowThursday 0.000855 ***
## dowTuesday 1.39e-08 ***
## dowWednesday 0.004581 **
## novel_locations:lockdown 0.403009
## ---
## 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: 63501
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.8350 -0.5436 0.0511 0.6045 4.0724
##
## Random effects:
## Groups Name Variance Std.Dev.
## subject (Intercept) 109.8 10.48
## Residual 294.5 17.16
## Number of obs: 7382, groups: subject, 235
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 53.652246 0.950259 710.578973 56.461 < 2e-16
## novel_locations 0.032194 0.004341 7230.537605 7.416 1.35e-13
## lockdown -5.100464 0.533108 7254.067154 -9.567 < 2e-16
## dowMonday -1.803315 0.773458 7152.880208 -2.331 0.01975
## dowSaturday 3.200919 0.800371 7156.569011 3.999 6.42e-05
## dowSunday 0.907098 0.793241 7154.954141 1.144 0.25286
## dowThursday -2.363555 0.763419 7155.043298 -3.096 0.00197
## dowTuesday -4.307515 0.758545 7153.607511 -5.679 1.41e-08
## dowWednesday -2.116064 0.783565 7153.513655 -2.701 0.00694
## novel_locations:lockdown -0.010190 0.010872 7239.104616 -0.937 0.34862
##
## (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 -0.293
## lockdown -0.267 0.454
## dowMonday -0.457 0.066 0.000
## dowSaturday -0.420 -0.014 -0.006 0.526
## dowSunday -0.448 0.043 0.027 0.534 0.513
## dowThursday -0.464 0.054 0.022 0.557 0.536 0.541
## dowTuesday -0.489 0.092 0.081 0.560 0.534 0.546 0.568
## dowWednesdy -0.454 0.052 0.024 0.541 0.518 0.526 0.547 0.552
## nvl_lctns:l 0.112 -0.367 -0.528 -0.006 -0.066 -0.011 -0.034 -0.029 -0.007
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$lockdown == 1), ]
##
## REML criterion at convergence: 24811
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.5388 -0.5538 0.0620 0.5701 4.1415
##
## Random effects:
## Groups Name Variance Std.Dev.
## subject (Intercept) 166.5 12.90
## Residual 264.4 16.26
## Number of obs: 2896, groups: subject, 208
##
## Fixed effects:
## Estimate Std. Error df t value
## (Intercept) 41.8586144 7.5689355 347.1193046 5.530
## roaming_entropy -1.3575264 3.3859277 2864.6485184 -0.401
## pre_covid_re 0.8416085 2.7787265 264.3027626 0.303
## time_of_day -0.0009883 0.0183795 2738.9726565 -0.054
## precipi -4.0697310 1.1546343 2722.8342591 -3.525
## mean_temp 0.0383689 0.0448484 1060.8629415 0.856
## distance -0.0038547 0.0073194 2732.0005017 -0.527
## dowMonday -1.3572994 1.1471750 2705.2372126 -1.183
## dowSaturday 2.7652455 1.2121384 2721.6519284 2.281
## dowSunday 2.9552637 1.2358285 2706.3122475 2.391
## dowThursday -0.6335195 1.1500512 2702.8094389 -0.551
## dowTuesday 1.0514301 1.2396782 2702.1866935 0.848
## dowWednesday 0.8163617 1.2094554 2712.6355430 0.675
## roaming_entropy:pre_covid_re 1.5325075 1.3895678 2867.1441350 1.103
## Pr(>|t|)
## (Intercept) 0.000000063 ***
## roaming_entropy 0.688500
## pre_covid_re 0.762223
## time_of_day 0.957120
## precipi 0.000431 ***
## mean_temp 0.392453
## distance 0.598482
## dowMonday 0.236847
## dowSaturday 0.022608 *
## dowSunday 0.016856 *
## dowThursday 0.581774
## dowTuesday 0.396431
## dowWednesday 0.499744
## roaming_entropy:pre_covid_re 0.270178
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: PA_avg ~ roaming_entropy * pre_covid_re + +dow + (1 | subject)
## Data: df[which(df$lockdown == 1), ]
##
## REML criterion at convergence: 24807.9
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.5237 -0.5383 0.0649 0.5686 3.9392
##
## Random effects:
## Groups Name Variance Std.Dev.
## subject (Intercept) 166.6 12.91
## Residual 265.3 16.29
## Number of obs: 2896, groups: subject, 208
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 44.4463 6.5589 261.1861 6.777 8.14e-11
## roaming_entropy -0.9564 3.3883 2868.6240 -0.282 0.7777
## pre_covid_re 0.6749 2.7566 259.8409 0.245 0.8068
## dowMonday -1.7111 1.1438 2706.5711 -1.496 0.1348
## dowSaturday 1.7693 1.1825 2716.3926 1.496 0.1347
## dowSunday 2.4902 1.2283 2703.3797 2.027 0.0427
## dowThursday -0.6386 1.1520 2705.9803 -0.554 0.5794
## dowTuesday 0.4690 1.2278 2700.3817 0.382 0.7025
## dowWednesday 0.4140 1.2035 2708.3295 0.344 0.7309
## roaming_entropy:pre_covid_re 1.3480 1.3883 2870.3372 0.971 0.3316
##
## (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 -0.334
## pre_covid_r -0.979 0.334
## dowMonday -0.099 -0.012 -0.004
## dowSaturday -0.101 -0.016 0.010 0.559
## dowSunday -0.086 -0.028 -0.008 0.540 0.522
## dowThursday -0.098 -0.021 -0.001 0.575 0.561 0.536
## dowTuesday -0.081 -0.036 -0.013 0.538 0.520 0.500 0.536
## dowWednesdy -0.092 -0.016 -0.006 0.556 0.531 0.512 0.546 0.512
## rmng_ntr:__ 0.341 -0.989 -0.351 0.017 -0.001 0.028 0.017 0.036 0.020
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$lockdown == 1), ]
##
## REML criterion at convergence: 24834.8
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.4867 -0.5461 0.0601 0.5672 4.1046
##
## Random effects:
## Groups Name Variance Std.Dev.
## subject (Intercept) 165.3 12.86
## Residual 265.4 16.29
## Number of obs: 2896, groups: subject, 208
##
## Fixed effects:
## Estimate Std. Error df t value
## (Intercept) 39.309860 7.270180 304.725753 5.407
## novel_locations 0.062503 0.093859 2852.882109 0.666
## pre_covid_re 2.456724 2.625980 217.202096 0.936
## time_of_day -0.002680 0.018407 2739.566888 -0.146
## precipi -4.137219 1.155881 2723.195935 -3.579
## mean_temp 0.040467 0.044847 1051.200153 0.902
## distance -0.004445 0.007819 2716.886548 -0.568
## dowMonday -1.425459 1.149389 2705.636350 -1.240
## dowSaturday 2.874666 1.214204 2719.844128 2.368
## dowSunday 2.971939 1.237622 2706.095208 2.401
## dowThursday -0.623778 1.152305 2702.537329 -0.541
## dowTuesday 1.081399 1.241030 2701.848980 0.871
## dowWednesday 0.742040 1.211656 2712.814987 0.612
## novel_locations:pre_covid_re -0.009149 0.037389 2853.207303 -0.245
## Pr(>|t|)
## (Intercept) 0.00000013 ***
## novel_locations 0.505514
## pre_covid_re 0.350546
## time_of_day 0.884245
## precipi 0.000351 ***
## mean_temp 0.367078
## distance 0.569788
## dowMonday 0.215013
## dowSaturday 0.017977 *
## dowSunday 0.016403 *
## dowThursday 0.588324
## dowTuesday 0.383628
## dowWednesday 0.540312
## novel_locations:pre_covid_re 0.806698
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: PA_avg ~ novel_locations * pre_covid_re + dow + (1 | subject)
## Data: df[which(df$lockdown == 1), ]
##
## REML criterion at convergence: 24832.4
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.4888 -0.5360 0.0580 0.5632 4.0054
##
## Random effects:
## Groups Name Variance Std.Dev.
## subject (Intercept) 165.4 12.86
## Residual 266.4 16.32
## Number of obs: 2896, groups: subject, 208
##
## Fixed effects:
## Estimate Std. Error df t value
## (Intercept) 42.275370 6.234214 218.562476 6.781
## novel_locations 0.059268 0.093433 2857.692402 0.634
## pre_covid_re 2.165652 2.606072 213.148319 0.831
## dowMonday -1.782873 1.146159 2706.949264 -1.556
## dowSaturday 1.879544 1.185827 2714.028572 1.585
## dowSunday 2.502277 1.230318 2703.170927 2.034
## dowThursday -0.621276 1.154321 2705.639679 -0.538
## dowTuesday 0.494670 1.229497 2700.036549 0.402
## dowWednesday 0.335930 1.205796 2708.662731 0.279
## novel_locations:pre_covid_re -0.008972 0.037405 2857.373412 -0.240
## Pr(>|t|)
## (Intercept) 1.1e-10 ***
## novel_locations 0.5259
## pre_covid_re 0.4069
## dowMonday 0.1199
## dowSaturday 0.1131
## dowSunday 0.0421 *
## dowThursday 0.5905
## dowTuesday 0.6875
## dowWednesday 0.7806
## novel_locations:pre_covid_re 0.8105
## ---
## 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 -0.157
## pre_covid_r -0.979 0.158
## dowMonday -0.106 -0.021 -0.001
## dowSaturday -0.106 -0.025 0.006 0.558
## dowSunday -0.099 -0.011 -0.001 0.540 0.521
## dowThursday -0.106 -0.026 0.001 0.575 0.560 0.536
## dowTuesday -0.098 0.003 -0.001 0.538 0.518 0.500 0.535
## dowWednesdy -0.100 -0.021 -0.002 0.556 0.531 0.512 0.547 0.512
## nvl_lctn:__ 0.163 -0.994 -0.167 0.024 0.012 0.012 0.023 -0.001 0.023
```