Time to Check EMA Analyses
Emily Moraes
2/5/2021
Density Plots
Mixed Effect Models
Density Plots
Time to Check summary stats
| vars | n | mean | sd | min | max | range | se | |
|---|---|---|---|---|---|---|---|---|
| X1 | 1 | 3264 | 48.26072 | 585.2739 | 0 | 30114 | 30114 | 10.24434 |
- 4.2% of TTCs were above 150 mins (151-9300 mins)
## $exam_num
##
## Call:
## lm(formula = TimetoCheck ~ exam_num, data = df)
##
## Residuals:
## Min 1Q Median 3Q Max
## -78.8 -53.5 -29.4 -20.0 30035.2
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 27.022 20.435 1.322 0.1861
## exam_num2 51.774 28.265 1.832 0.0671 .
## exam_num3 5.334 28.602 0.186 0.8521
## exam_num4 26.440 30.218 0.875 0.3817
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 585.2 on 3260 degrees of freedom
## Multiple R-squared: 0.00129, Adjusted R-squared: 0.0003712
## F-statistic: 1.404 on 3 and 3260 DF, p-value: 0.2397
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: TimetoCheck ~ exam_num + Prediction_1 + (1 | ID)
## Data: df
##
## REML criterion at convergence: 33101.6
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -0.105 -0.065 -0.035 -0.020 45.234
##
## Random effects:
## Groups Name Variance Std.Dev.
## ID (Intercept) 155.8 12.48
## Residual 440975.6 664.06
## Number of obs: 2093, groups: ID, 719
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) -6.3802 68.9899 1891.1632 -0.092 0.926
## exam_num2 34.8231 38.8139 1818.9175 0.897 0.370
## exam_num3 2.1819 40.6418 1855.9218 0.054 0.957
## exam_num4 -0.4156 45.7013 1905.0188 -0.009 0.993
## Prediction_1 0.4100 0.8763 1693.6453 0.468 0.640
##
## Correlation of Fixed Effects:
## (Intr) exm_n2 exm_n3 exm_n4
## exam_num2 -0.250
## exam_num3 -0.421 0.510
## exam_num4 -0.142 0.469 0.422
## Predictin_1 -0.910 -0.061 0.142 -0.129Mixed Effect Models
PTQ
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: TimetoCheck ~ PTQscore + (1 | ID)
## Data: df
##
## REML criterion at convergence: 9508.8
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -0.6241 -0.1703 -0.0991 -0.0309 18.2222
##
## Random effects:
## Groups Name Variance Std.Dev.
## ID (Intercept) 4882 69.87
## Residual 243194 493.15
## Number of obs: 624, groups: ID, 183
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 8.794 39.743 117.671 0.221 0.8253
## PTQscore 3.312 1.696 125.086 1.953 0.0531 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr)
## PTQscore -0.857PHQ
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: TimetoCheck ~ DEPscore + (1 | ID)
## Data: df
##
## REML criterion at convergence: 10040.5
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -1.4869 -0.1340 -0.1166 -0.0872 17.9808
##
## Random effects:
## Groups Name Variance Std.Dev.
## ID (Intercept) 21494 146.6
## Residual 228588 478.1
## Number of obs: 659, groups: ID, 184
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 77.537 30.237 186.026 2.564 0.0111 *
## DEPscore 1.705 4.068 333.519 0.419 0.6754
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr)
## DEPscore -0.698GAD
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: TimetoCheck ~ GADscore + (1 | ID)
## Data: df
##
## REML criterion at convergence: 10038.2
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -1.4446 -0.1454 -0.0958 -0.0673 17.9748
##
## Random effects:
## Groups Name Variance Std.Dev.
## ID (Intercept) 20782 144.2
## Residual 228397 477.9
## Number of obs: 659, groups: ID, 184
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 53.877 30.661 187.868 1.757 0.0805 .
## GADscore 6.661 4.476 314.504 1.488 0.1377
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr)
## GADscore -0.711Grade Predictions
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: TimetoCheck ~ Prediction_1 + (1 | ID)
## Data: df
##
## REML criterion at convergence: 33130.1
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -0.076 -0.055 -0.046 -0.030 45.288
##
## Random effects:
## Groups Name Variance Std.Dev.
## ID (Intercept) 133.1 11.54
## Residual 440612.9 663.79
## Number of obs: 2093, groups: ID, 719
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) -0.4648 62.3759 1776.1967 -0.007 0.994
## Prediction_1 0.4843 0.8437 1767.7698 0.574 0.566
##
## Correlation of Fixed Effects:
## (Intr)
## Predictin_1 -0.973
Interaction: Grade prediction * PTQ Score
