TTC_Analyses_2.0
Emily Moraes
3/4/2021
Summaries
Times
TTC Stats by Time Type
##
## Descriptive statistics by group
## group: ttc_Start
## vars n mean sd median trimmed mad min max range skew kurtosis
## X1 1 3014 52.7 757.36 4 7.51 5.93 0 30114 30114 34.57 1273.98
## se
## X1 13.8
## ------------------------------------------------------------
## group: ttc_End
## vars n mean sd median trimmed mad min max range skew kurtosis se
## X1 1 3014 56.51 768.83 5 8.84 5.93 0 30115 30115 33.32 1201.7 14
## ------------------------------------------------------------
## group: TimetoComplete
## vars n mean sd median trimmed mad min max range skew kurtosis se
## X1 1 3014 3.81 108.71 1 0.61 1.48 0 5884 5884 52.69 2838.52 1.98
TTC_Start by Exam
##
## Descriptive statistics by group
## group: 1
## vars n mean sd median trimmed mad min max range skew kurtosis se
## X1 1 820 24.3 91.07 4 7.54 5.93 0 1248 1248 9.11 101.91 3.18
## ------------------------------------------------------------
## group: 2
## vars n mean sd median trimmed mad min max range skew kurtosis
## X1 1 898 71.89 1058.3 3 6.9 4.45 0 30114 30114 26.23 726.57
## se
## X1 35.32
## ------------------------------------------------------------
## group: 3
## vars n mean sd median trimmed mad min max range skew kurtosis se
## X1 1 853 32 141.44 5 8.3 7.41 0 1918 1918 9.13 92.64 4.84
## ------------------------------------------------------------
## group: 4
## vars n mean sd median trimmed mad min max range skew kurtosis
## X1 1 443 106.26 1255.87 3 7.65 4.45 0 25833 25833 19.54 395
## se
## X1 59.67Symptom Measures
PTQ Scores
## df$PTQscore
## n missing distinct Info Mean Gmd .05 .10
## 2978 36 58 0.999 20.41 14.88 1 3
## .25 .50 .75 .90 .95
## 10 20 29 38 43
##
## lowest : 0 1 2 3 4, highest: 53 54 55 56 60
PTQ by Cohort
##
## Descriptive statistics by group
## group: 3000
## vars n mean sd median trimmed mad min max range skew kurtosis se
## X1 1 620 20.11 12.07 19 19.7 13.34 0 60 60 0.26 -0.71 0.48
## ------------------------------------------------------------
## group: 4000
## vars n mean sd median trimmed mad min max range skew kurtosis se
## X1 1 924 20.78 12.99 21 20.22 14.83 0 60 60 0.31 -0.52 0.43
## ------------------------------------------------------------
## group: 5000
## vars n mean sd median trimmed mad min max range skew kurtosis se
## X1 1 1434 20.29 13.49 19 19.67 14.83 0 60 60 0.34 -0.58 0.36
Predictions
Prediction 1
## df$Prediction_1
## n missing distinct Info Mean Gmd .05 .10
## 2538 476 69 0.988 72.51 17.69 40 50
## .25 .50 .75 .90 .95
## 65 75 85 90 92
##
## lowest : 0 2 3 5 6, highest: 95 96 97 98 100
Prediction 2
## df$Prediction_2
## n missing distinct Info Mean Gmd .05 .10
## 2773 241 80 0.989 69.29 18.61 34 50
## .25 .50 .75 .90 .95
## 60 70 80 90 90
##
## lowest : 0 1 2 3 5, highest: 95 96 97 98 100
Are Predictions 1 and 2 different?
##
## Paired t-test
##
## data: df$Prediction_1 and df$Prediction_2
## t = 17.642, df = 2536, p-value < 2.2e-16
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## 2.441838 3.052526
## sample estimates:
## mean of the differences
## 2.747182All observations
TTC Start
## df$ttc_Start
## n missing distinct Info Mean Gmd .05 .10
## 3014 0 226 0.982 52.7 97.33 0 0
## .25 .50 .75 .90 .95
## 0 4 12 51 114
##
## lowest : 0 1 2 3 4, highest: 1998 4852 9298 25833 30114
##
## Value 0 500 1000 1500 2000 5000 9500 26000 30000
## Frequency 2948 40 10 10 2 1 1 1 1
## Proportion 0.978 0.013 0.003 0.003 0.001 0.000 0.000 0.000 0.000
##
## For the frequency table, variable is rounded to the nearest 500Cut off 1 (< 2,000 mins)
TTC Start
## ttcmod$ttc_Start
## n missing distinct Info Mean Gmd .05 .10
## 3010 0 222 0.982 29.49 51.05 0.0 0.0
## .25 .50 .75 .90 .95
## 0.0 4.0 12.0 50.0 110.5
##
## lowest : 0 1 2 3 4, highest: 1569 1570 1607 1918 1998Cut off 2 (< 1,000 mins)
TTC Start
## ttcmod2$ttc_Start
## n missing distinct Info Mean Gmd .05 .10
## 2989 0 201 0.982 19.99 32.62 0.0 0.0
## .25 .50 .75 .90 .95
## 0.0 4.0 11.0 47.0 94.8
##
## lowest : 0 1 2 3 4, highest: 553 626 670 696 785TTC Start and PTQ
All observations
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: ttc_Start ~ PTQscore + (1 | ID)
## Data: df
##
## REML criterion at convergence: 46485.9
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -0.221 -0.092 -0.049 -0.005 50.485
##
## Random effects:
## Groups Name Variance Std.Dev.
## ID (Intercept) 0 0.0
## Residual 353379 594.5
## Number of obs: 2978, groups: ID, 919
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) -5.234 20.225 2976.000 -0.259 0.79580
## PTQscore 2.298 0.835 2976.000 2.752 0.00595 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr)
## PTQscore -0.843
## convergence code: 0
## boundary (singular) fit: see ?isSingularAll obs (log)
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: ttc_Start_log ~ PTQscore + (1 | ID)
## Data: df
##
## REML criterion at convergence: 10760.8
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -2.7269 -0.6128 -0.1572 0.4601 6.0826
##
## Random effects:
## Groups Name Variance Std.Dev.
## ID (Intercept) 0.7294 0.854
## Residual 1.6510 1.285
## Number of obs: 2978, groups: ID, 919
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 1.627e+00 6.871e-02 8.864e+02 23.673 <2e-16 ***
## PTQscore 5.144e-03 2.821e-03 9.062e+02 1.823 0.0686 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr)
## PTQscore -0.842Cut off 1 (< 2,000 mins)
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: ttc_Start ~ PTQscore + (1 | ID)
## Data: ttcmod
##
## REML criterion at convergence: 36700.8
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.0298 -0.1779 -0.1417 -0.0932 15.8323
##
## Random effects:
## Groups Name Variance Std.Dev.
## ID (Intercept) 1980 44.5
## Residual 11688 108.1
## Number of obs: 2975, groups: ID, 919
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 21.2403 4.6131 780.1172 4.604 4.83e-06 ***
## PTQscore 0.2918 0.1900 802.4902 1.535 0.125
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr)
## PTQscore -0.842Cut off 1 (log)
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: ttc_Start_log ~ PTQscore + (1 | ID)
## Data: ttcmod
##
## REML criterion at convergence: 10657.7
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -2.8151 -0.6117 -0.1579 0.4679 4.5765
##
## Random effects:
## Groups Name Variance Std.Dev.
## ID (Intercept) 0.7432 0.8621
## Residual 1.5831 1.2582
## Number of obs: 2975, groups: ID, 919
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 1.635e+00 6.851e-02 8.853e+02 23.867 <2e-16 ***
## PTQscore 4.347e-03 2.814e-03 9.061e+02 1.545 0.123
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr)
## PTQscore -0.842Cut off 1 (< 1,000 mins)
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: ttc_Start ~ PTQscore + (1 | ID)
## Data: ttcmod2
##
## REML criterion at convergence: 31923.7
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -2.4340 -0.2691 -0.2283 -0.1182 12.1786
##
## Random effects:
## Groups Name Variance Std.Dev.
## ID (Intercept) 398.5 19.96
## Residual 2509.8 50.10
## Number of obs: 2958, groups: ID, 918
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 18.73203 2.11856 845.57902 8.842 <2e-16 ***
## PTQscore 0.03020 0.08741 870.52873 0.345 0.73
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr)
## PTQscore -0.842TTC Start and Prediction 1
All observations
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: ttc_Start ~ Prediction_1 + (1 | ID)
## Data: df
##
## REML criterion at convergence: 39714.3
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -0.109 -0.061 -0.053 -0.035 49.597
##
## Random effects:
## Groups Name Variance Std.Dev.
## ID (Intercept) 299.3 17.3
## Residual 366999.4 605.8
## Number of obs: 2538, groups: ID, 895
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 5.1393 53.4076 2155.8490 0.096 0.923
## Prediction_1 0.4258 0.7176 2142.9259 0.593 0.553
##
## Correlation of Fixed Effects:
## (Intr)
## Predictin_1 -0.974All obs (log)
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: ttc_Start_log ~ Prediction_1 + (1 | ID)
## Data: df
##
## REML criterion at convergence: 9033.5
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -2.8354 -0.6038 -0.1375 0.4591 6.3639
##
## Random effects:
## Groups Name Variance Std.Dev.
## ID (Intercept) 0.7085 0.8417
## Residual 1.5344 1.2387
## Number of obs: 2538, groups: ID, 895
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 1.754e+00 1.368e-01 2.382e+03 12.820 <2e-16 ***
## Prediction_1 -1.033e-03 1.831e-03 2.443e+03 -0.564 0.573
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr)
## Predictin_1 -0.961Cut off 1 (< 2,000 mins)
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: ttc_Start ~ Prediction_1 + (1 | ID)
## Data: ttcmod
##
## REML criterion at convergence: 30629.7
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.0456 -0.1907 -0.1416 -0.0848 14.2807
##
## Random effects:
## Groups Name Variance Std.Dev.
## ID (Intercept) 1429 37.81
## Residual 9026 95.00
## Number of obs: 2537, groups: ID, 895
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 46.9423 9.3374 2160.0583 5.027 5.38e-07 ***
## Prediction_1 -0.3137 0.1255 2184.3578 -2.500 0.0125 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr)
## Predictin_1 -0.969Cut off 1 (log)
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: ttc_Start_log ~ Prediction_1 + (1 | ID)
## Data: ttcmod
##
## REML criterion at convergence: 8982
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -2.9013 -0.6112 -0.1421 0.4620 3.9214
##
## Random effects:
## Groups Name Variance Std.Dev.
## ID (Intercept) 0.7255 0.8517
## Residual 1.4901 1.2207
## Number of obs: 2537, groups: ID, 895
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 1.771e+00 1.358e-01 2.392e+03 13.048 <2e-16 ***
## Prediction_1 -1.320e-03 1.816e-03 2.454e+03 -0.727 0.467
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr)
## Predictin_1 -0.960Cut off 2 (< 1,000 mins)
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: ttc_Start ~ Prediction_1 + (1 | ID)
## Data: ttcmod2
##
## REML criterion at convergence: 27189.9
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -2.6588 -0.2610 -0.2092 -0.1127 12.3449
##
## Random effects:
## Groups Name Variance Std.Dev.
## ID (Intercept) 440.5 20.99
## Residual 2405.6 49.05
## Number of obs: 2525, groups: ID, 895
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 22.55677 4.91937 2138.70048 4.585 4.8e-06 ***
## Prediction_1 -0.05738 0.06606 2169.23496 -0.869 0.385
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr)
## Predictin_1 -0.969TTC Start and Prediction 1 (controlling for confidence)
All observations
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: ttc_Start ~ Prediction_1 + Prediction_1_confidence + (1 | ID)
## Data: df
##
## REML criterion at convergence: 39640.1
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -0.126 -0.064 -0.049 -0.029 49.524
##
## Random effects:
## Groups Name Variance Std.Dev.
## ID (Intercept) 493.4 22.21
## Residual 367611.4 606.31
## Number of obs: 2533, groups: ID, 895
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) -16.4236 62.6258 2055.1585 -0.262 0.793
## Prediction_1 0.4425 0.7221 2129.4239 0.613 0.540
## Prediction_1_confidence 0.3319 0.4961 2036.1465 0.669 0.504
##
## Correlation of Fixed Effects:
## (Intr) Prdc_1
## Predictin_1 -0.853
## Prdctn_1_cn -0.514 0.034All obs (log)
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: ttc_Start_log ~ Prediction_1 + Prediction_1_confidence + (1 | ID)
## Data: df
##
## REML criterion at convergence: 9020.2
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -2.8349 -0.6160 -0.1367 0.4627 6.4087
##
## Random effects:
## Groups Name Variance Std.Dev.
## ID (Intercept) 0.7142 0.8451
## Residual 1.5267 1.2356
## Number of obs: 2533, groups: ID, 895
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 1.873e+00 1.616e-01 2.364e+03 11.590 <2e-16 ***
## Prediction_1 -1.231e-03 1.840e-03 2.437e+03 -0.669 0.503
## Prediction_1_confidence -1.767e-03 1.274e-03 2.432e+03 -1.387 0.166
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) Prdc_1
## Predictin_1 -0.844
## Prdctn_1_cn -0.527 0.054Cut off 1 (< 2,000)
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: ttc_Start ~ Prediction_1 + Prediction_1_confidence + (1 | ID)
## Data: ttcmod
##
## REML criterion at convergence: 30575.8
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.0327 -0.1914 -0.1398 -0.0838 14.2376
##
## Random effects:
## Groups Name Variance Std.Dev.
## ID (Intercept) 1430 37.82
## Residual 9042 95.09
## Number of obs: 2532, groups: ID, 895
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 40.84194 11.01009 2076.60215 3.710 0.000213 ***
## Prediction_1 -0.31189 0.12625 2170.57257 -2.470 0.013575 *
## Prediction_1_confidence 0.09729 0.08719 2106.13564 1.116 0.264633
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) Prdc_1
## Predictin_1 -0.849
## Prdctn_1_cn -0.522 0.045Cut off 1 (log)
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: ttc_Start_log ~ Prediction_1 + Prediction_1_confidence + (1 | ID)
## Data: ttcmod
##
## REML criterion at convergence: 8967.9
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -2.9140 -0.6177 -0.1426 0.4679 3.9227
##
## Random effects:
## Groups Name Variance Std.Dev.
## ID (Intercept) 0.7318 0.8555
## Residual 1.4816 1.2172
## Number of obs: 2532, groups: ID, 895
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 1.906e+00 1.604e-01 2.377e+03 11.882 <2e-16 ***
## Prediction_1 -1.542e-03 1.825e-03 2.448e+03 -0.845 0.398
## Prediction_1_confidence -1.990e-03 1.264e-03 2.444e+03 -1.574 0.116
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) Prdc_1
## Predictin_1 -0.844
## Prdctn_1_cn -0.527 0.055Cut off 2 (< 1,000)
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: ttc_Start ~ Prediction_1 + Prediction_1_confidence + (1 | ID)
## Data: ttcmod2
##
## REML criterion at convergence: 27143.8
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -2.6607 -0.2616 -0.2092 -0.1117 12.3403
##
## Random effects:
## Groups Name Variance Std.Dev.
## ID (Intercept) 444.1 21.07
## Residual 2407.7 49.07
## Number of obs: 2520, groups: ID, 895
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 23.93461 5.77868 2050.46715 4.142 3.58e-05 ***
## Prediction_1 -0.06028 0.06648 2157.06908 -0.907 0.365
## Prediction_1_confidence -0.01959 0.04574 2085.81065 -0.428 0.668
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) Prdc_1
## Predictin_1 -0.849
## Prdctn_1_cn -0.517 0.039TTC Start and Prediction 2
All observations
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: ttc_Start_log ~ Prediction_2 + (1 | ID)
## Data: df
##
## REML criterion at convergence: 9920.9
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -2.8233 -0.6072 -0.1479 0.4600 6.2899
##
## Random effects:
## Groups Name Variance Std.Dev.
## ID (Intercept) 0.7455 0.8634
## Residual 1.5624 1.2499
## Number of obs: 2773, groups: ID, 912
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 1.851e+00 1.251e-01 2.550e+03 14.797 <2e-16 ***
## Prediction_2 -2.117e-03 1.738e-03 2.655e+03 -1.218 0.223
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr)
## Predictin_2 -0.954Cut off 1 (< 2,000 mins)
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: ttc_Start ~ Prediction_2 + (1 | ID)
## Data: ttcmod
##
## REML criterion at convergence: 34009.9
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -4.3378 -0.1654 -0.1170 -0.0695 14.9773
##
## Random effects:
## Groups Name Variance Std.Dev.
## ID (Intercept) 3116 55.82
## Residual 10136 100.68
## Number of obs: 2771, groups: ID, 912
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 45.0019 9.5285 2266.4700 4.723 2.47e-06 ***
## Prediction_2 -0.2639 0.1329 2387.6818 -1.986 0.0471 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr)
## Predictin_2 -0.959Cut off 1 (log)
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: ttc_Start_log ~ Prediction_2 + (1 | ID)
## Data: ttcmod
##
## REML criterion at convergence: 9841.4
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -2.9062 -0.6120 -0.1501 0.4676 3.8963
##
## Random effects:
## Groups Name Variance Std.Dev.
## ID (Intercept) 0.7627 0.8733
## Residual 1.5045 1.2266
## Number of obs: 2771, groups: ID, 912
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 1.843e+00 1.238e-01 2.566e+03 14.89 <2e-16 ***
## Prediction_2 -2.097e-03 1.718e-03 2.672e+03 -1.22 0.222
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr)
## Predictin_2 -0.953Cut off 2 (< 1,000 mins)
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: ttc_Start ~ Prediction_2 + (1 | ID)
## Data: ttcmod2
##
## REML criterion at convergence: 29591.3
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -2.7619 -0.2608 -0.2096 -0.1079 12.4951
##
## Random effects:
## Groups Name Variance Std.Dev.
## ID (Intercept) 446.5 21.13
## Residual 2332.0 48.29
## Number of obs: 2755, groups: ID, 910
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 22.20405 4.36924 2214.69146 5.082 4.05e-07 ***
## Prediction_2 -0.05327 0.06104 2282.36469 -0.873 0.383
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr)
## Predictin_2 -0.963TTC Start and Prediction 2 (controlling for confidence)
All observations
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: ttc_Start ~ Prediction_2 + Prediction_2_confidence + (1 | ID)
## Data: df
##
## REML criterion at convergence: 33600.3
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -0.106 -0.061 -0.043 -0.026 44.979
##
## Random effects:
## Groups Name Variance Std.Dev.
## ID (Intercept) 0 0.0
## Residual 446722 668.4
## Number of obs: 2121, groups: ID, 729
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 7.061e+01 6.918e+01 2.118e+03 1.021 0.308
## Prediction_2 5.305e-03 8.259e-01 2.118e+03 0.006 0.995
## Prediction_2_confidence -5.962e-01 5.888e-01 2.118e+03 -1.013 0.311
##
## Correlation of Fixed Effects:
## (Intr) Prdc_2
## Predictin_2 -0.848
## Prdctn_2_cn -0.543 0.068
## convergence code: 0
## boundary (singular) fit: see ?isSingularAll obs (log)
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: ttc_Start_log ~ Prediction_2 + Prediction_2_confidence + (1 | ID)
## Data: df
##
## REML criterion at convergence: 7567.6
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -2.5982 -0.6379 -0.1526 0.4473 6.3130
##
## Random effects:
## Groups Name Variance Std.Dev.
## ID (Intercept) 0.6027 0.7763
## Residual 1.5996 1.2648
## Number of obs: 2121, groups: ID, 729
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 1.918e+00 1.628e-01 1.847e+03 11.778 <2e-16 ***
## Prediction_2 -3.368e-03 1.915e-03 1.973e+03 -1.759 0.0788 .
## Prediction_2_confidence -2.768e-03 1.417e-03 1.738e+03 -1.954 0.0509 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) Prdc_2
## Predictin_2 -0.832
## Prdctn_2_cn -0.554 0.071Cut off 1 (< 2,000)
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: ttc_Start ~ Prediction_2 + Prediction_2_confidence + (1 | ID)
## Data: ttcmod
##
## REML criterion at convergence: 25159.2
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.7769 -0.1850 -0.1214 -0.0591 15.7424
##
## Random effects:
## Groups Name Variance Std.Dev.
## ID (Intercept) 1408 37.52
## Residual 7213 84.93
## Number of obs: 2119, groups: ID, 729
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 35.20375 10.12268 1609.84737 3.478 0.000519 ***
## Prediction_2 -0.33299 0.11978 1747.99741 -2.780 0.005494 **
## Prediction_2_confidence 0.14589 0.08747 1433.61040 1.668 0.095557 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) Prdc_2
## Predictin_2 -0.839
## Prdctn_2_cn -0.551 0.070Cut off 1 (log)
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: ttc_Start_log ~ Prediction_2 + Prediction_2_confidence + (1 | ID)
## Data: ttcmod
##
## REML criterion at convergence: 7488.3
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -2.7117 -0.6341 -0.1560 0.4579 3.9557
##
## Random effects:
## Groups Name Variance Std.Dev.
## ID (Intercept) 0.6257 0.791
## Residual 1.5221 1.234
## Number of obs: 2119, groups: ID, 729
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 1.887e+00 1.609e-01 1.870e+03 11.730 <2e-16 ***
## Prediction_2 -3.318e-03 1.888e-03 1.994e+03 -1.757 0.0790 .
## Prediction_2_confidence -2.407e-03 1.400e-03 1.773e+03 -1.719 0.0858 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) Prdc_2
## Predictin_2 -0.831
## Prdctn_2_cn -0.555 0.072Cut off 2 (< 1,000)
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: ttc_Start ~ Prediction_2 + Prediction_2_confidence + (1 | ID)
## Data: ttcmod2
##
## REML criterion at convergence: 22144.1
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -2.0708 -0.2557 -0.1930 -0.0948 12.7357
##
## Random effects:
## Groups Name Variance Std.Dev.
## ID (Intercept) 368.5 19.20
## Residual 1803.8 42.47
## Number of obs: 2110, groups: ID, 728
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 25.80816 5.09991 1514.24961 5.061 4.69e-07 ***
## Prediction_2 -0.10193 0.06054 1676.66078 -1.684 0.0924 .
## Prediction_2_confidence -0.05748 0.04412 1315.16129 -1.303 0.1929
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) Prdc_2
## Predictin_2 -0.838
## Prdctn_2_cn -0.546 0.063TTC Start and Prediction change
All observations
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: ttc_Start ~ I(Prediction_1 - Prediction_2) + (1 | ID)
## Data: df
##
## REML criterion at convergence: 39697.5
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -0.276 -0.058 -0.049 -0.033 49.585
##
## Random effects:
## Groups Name Variance Std.Dev.
## ID (Intercept) 342.3 18.5
## Residual 367008.7 605.8
## Number of obs: 2537, groups: ID, 895
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 31.828 12.762 1242.785 2.494 0.0128 *
## I(Prediction_1 - Prediction_2) 1.526 1.535 2508.266 0.995 0.3201
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr)
## I(Pr_1-P_2) -0.330All obs (log)
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: ttc_Start_log ~ I(Prediction_1 - Prediction_2) + (1 | ID)
## Data: df
##
## REML criterion at convergence: 9028.2
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -2.8407 -0.6038 -0.1352 0.4589 6.3446
##
## Random effects:
## Groups Name Variance Std.Dev.
## ID (Intercept) 0.7052 0.8398
## Residual 1.5357 1.2392
## Number of obs: 2537, groups: ID, 895
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 1.676e+00 3.928e-02 9.396e+02 42.666 <2e-16
## I(Prediction_1 - Prediction_2) 1.533e-03 3.591e-03 2.430e+03 0.427 0.669
##
## (Intercept) ***
## I(Prediction_1 - Prediction_2)
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr)
## I(Pr_1-P_2) -0.257Cut off 1 (< 2,000)
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: ttc_Start ~ I(Prediction_1 - Prediction_2) + (1 | ID)
## Data: ttcmod
##
## REML criterion at convergence: 30623.4
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -2.9795 -0.1818 -0.1553 -0.1017 14.3060
##
## Random effects:
## Groups Name Variance Std.Dev.
## ID (Intercept) 1434 37.87
## Residual 9050 95.13
## Number of obs: 2536, groups: ID, 895
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 2.416e+01 2.414e+00 9.333e+02 10.009 <2e-16
## I(Prediction_1 - Prediction_2) 5.851e-02 2.582e-01 2.532e+03 0.227 0.821
##
## (Intercept) ***
## I(Prediction_1 - Prediction_2)
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr)
## I(Pr_1-P_2) -0.297Cut off 1 (log)
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: ttc_Start_log ~ I(Prediction_1 - Prediction_2) + (1 | ID)
## Data: ttcmod
##
## REML criterion at convergence: 8977
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -2.9090 -0.6110 -0.1373 0.4657 3.9190
##
## Random effects:
## Groups Name Variance Std.Dev.
## ID (Intercept) 0.7218 0.8496
## Residual 1.4918 1.2214
## Number of obs: 2536, groups: ID, 895
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 1.675e+00 3.926e-02 9.382e+02 42.65 <2e-16
## I(Prediction_1 - Prediction_2) 9.242e-04 3.553e-03 2.419e+03 0.26 0.795
##
## (Intercept) ***
## I(Prediction_1 - Prediction_2)
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr)
## I(Pr_1-P_2) -0.254Cut off 2 (< 1,000)
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: ttc_Start ~ I(Prediction_1 - Prediction_2) + (1 | ID)
## Data: ttcmod2
##
## REML criterion at convergence: 27179.3
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -2.6532 -0.2597 -0.2147 -0.1125 12.3280
##
## Random effects:
## Groups Name Variance Std.Dev.
## ID (Intercept) 438.3 20.94
## Residual 2409.0 49.08
## Number of obs: 2524, groups: ID, 895
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 18.3919 1.2751 841.9435 14.423 <2e-16
## I(Prediction_1 - Prediction_2) 0.0106 0.1345 2516.6537 0.079 0.937
##
## (Intercept) ***
## I(Prediction_1 - Prediction_2)
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr)
## I(Pr_1-P_2) -0.293