Brief Test of Attention
t-Test
Attention = t.test(widenp13$Attention.1,widenp13$Attention.3,paired=TRUE)
Attention
##
## Paired t-test
##
## data: widenp13$Attention.1 and widenp13$Attention.3
## t = 5.4296536, df = 1520, p-value = 6.564092e-08
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## 0.1809968476 0.3857355653
## sample estimates:
## mean of the differences
## 0.2833662064
Mixed Model Regression
Attn = lmer(Attention~Time + Age0 + Sex + Race + PovStat + (1|HNDid),data=np13_long)
summary(Attn)
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: Attention ~ Time + Age0 + Sex + Race + PovStat + (1 | HNDid)
## Data: np13_long
##
## REML criterion at convergence: 18119.6
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.3200460 -0.5232179 0.0182806 0.5598941 2.6975948
##
## Random effects:
## Groups Name Variance Std.Dev.
## HNDid (Intercept) 2.507538 1.583521
## Residual 2.091361 1.446154
## Number of obs: 4270, groups: HNDid, 2749
##
## Fixed effects:
## Estimate Std. Error df t value
## (Intercept) 9.101230e+00 2.188432e-01 2.945679e+03 41.58790
## Time -1.487830e-01 2.415217e-02 2.003775e+03 -6.16023
## Age0 -3.225988e-02 4.126391e-03 2.697835e+03 -7.81794
## SexMen -3.046929e-01 7.684270e-02 2.680643e+03 -3.96515
## RaceAfrAm -7.825774e-01 7.802616e-02 2.676487e+03 -10.02968
## PovStatBelow -6.228142e-01 7.834004e-02 2.677095e+03 -7.95014
## Pr(>|t|)
## (Intercept) < 2.22e-16
## Time 8.7548e-10
## Age0 7.6361e-15
## SexMen 7.5269e-05
## RaceAfrAm < 2.22e-16
## PovStatBelow 2.7212e-15
##
## Correlation of Fixed Effects:
## (Intr) Time Age0 SexMen RcAfrA
## Time -0.228
## Age0 -0.918 0.014
## SexMen -0.169 0.021 0.009
## RaceAfrAm -0.191 -0.020 0.010 -0.010
## PovStatBelw -0.186 0.032 0.062 0.059 -0.153
California Verbal Learning Test A
t-Test
CVLtca = t.test(widenp13$CVLtca.1,widenp13$CVLtca.3,paired=TRUE)
CVLtca
##
## Paired t-test
##
## data: widenp13$CVLtca.1 and widenp13$CVLtca.3
## t = 38.470457, df = 1613, p-value < 2.2204e-16
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## 6.447301055 7.140059540
## sample estimates:
## mean of the differences
## 6.793680297
Mixed Model Regression
CVL_listA = lmer(CVLtca~Time + Age0 + Sex + Race + PovStat + (1|HNDid),data=np13_long)
summary(CVL_listA)
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: CVLtca ~ Time + Age0 + Sex + Race + PovStat + (1 | HNDid)
## Data: np13_long
##
## REML criterion at convergence: 29606.4
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.6958650 -0.4689845 0.0260421 0.5035957 3.1351564
##
## Random effects:
## Groups Name Variance Std.Dev.
## HNDid (Intercept) 24.65441 4.965321
## Residual 25.31103 5.031007
## Number of obs: 4452, groups: HNDid, 2838
##
## Fixed effects:
## Estimate Std. Error df t value
## (Intercept) 39.20892160 0.70770563 3082.69792654 55.40287
## Time -3.33504771 0.08116774 2164.17794343 -41.08834
## Age0 -0.17288072 0.01329820 2810.89391533 -13.00031
## SexMen -2.83343778 0.24594727 2769.75989120 -11.52051
## RaceAfrAm -2.35663575 0.25050990 2765.56648907 -9.40736
## PovStatBelow -1.95671150 0.25058651 2763.26618068 -7.80853
## Pr(>|t|)
## (Intercept) < 2.22e-16
## Time < 2.22e-16
## Age0 < 2.22e-16
## SexMen < 2.22e-16
## RaceAfrAm < 2.22e-16
## PovStatBelow 8.1479e-15
##
## Correlation of Fixed Effects:
## (Intr) Time Age0 SexMen RcAfrA
## Time -0.237
## Age0 -0.915 0.007
## SexMen -0.167 0.017 0.008
## RaceAfrAm -0.189 -0.023 0.009 -0.009
## PovStatBelw -0.189 0.031 0.065 0.062 -0.153
California Verbal Learning Test B
t-Test
CVLtcb = t.test(widenp13$CVLtcb.1,widenp13$CVLtcb.3,paired=TRUE)
CVLtcb
##
## Paired t-test
##
## data: widenp13$CVLtcb.1 and widenp13$CVLtcb.3
## t = 31.924465, df = 1599, p-value < 2.2204e-16
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## 1.613736087 1.825013913
## sample estimates:
## mean of the differences
## 1.719375
Mixed Model Regression
CVL_listB= lmer(CVLtcb~Time + Age0 + Sex + Race + PovStat + (1|HNDid),data=np13_long)
summary(CVL_listB)
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: CVLtcb ~ Time + Age0 + Sex + Race + PovStat + (1 | HNDid)
## Data: np13_long
##
## REML criterion at convergence: 18144.8
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -2.5697678 -0.6005774 -0.0475523 0.5475930 3.7387468
##
## Random effects:
## Groups Name Variance Std.Dev.
## HNDid (Intercept) 1.344019 1.159318
## Residual 2.324447 1.524614
## Number of obs: 4435, groups: HNDid, 2835
##
## Fixed effects:
## Estimate Std. Error df t value
## (Intercept) 8.10202786 0.18810367 3118.56537106 43.07214
## Time -0.84417745 0.02417936 2290.24794134 -34.91314
## Age0 -0.02394167 0.00350989 2794.33921950 -6.82120
## SexMen -0.61909606 0.06485189 2746.31265153 -9.54631
## RaceAfrAm -0.63889745 0.06605645 2738.86055450 -9.67199
## PovStatBelow -0.43267703 0.06606889 2736.43725465 -6.54888
## Pr(>|t|)
## (Intercept) < 2.22e-16
## Time < 2.22e-16
## Age0 1.1024e-11
## SexMen < 2.22e-16
## RaceAfrAm < 2.22e-16
## PovStatBelow 6.8990e-11
##
## Correlation of Fixed Effects:
## (Intr) Time Age0 SexMen RcAfrA
## Time -0.264
## Age0 -0.908 0.006
## SexMen -0.166 0.016 0.009
## RaceAfrAm -0.189 -0.024 0.011 -0.009
## PovStatBelw -0.188 0.032 0.064 0.061 -0.153
California Verbal Learning Test Learning Slope
t-Test
CVLbet = t.test(widenp13$CVLbet.1,widenp13$CVLbet.3,paired=TRUE)
CVLbet
##
## Paired t-test
##
## data: widenp13$CVLbet.1 and widenp13$CVLbet.3
## t = 2.7448119, df = 1618, p-value = 0.006121499
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## 0.02899875272 0.17421310646
## sample estimates:
## mean of the differences
## 0.1016059296
Mixed Model Regression
CVL_learn = lmer(CVLbet~Time + Age0 + Sex + Race + PovStat + (1|HNDid),data=np13_long)
summary(CVL_learn)
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: CVLbet ~ Time + Age0 + Sex + Race + PovStat + (1 | HNDid)
## Data: np13_long
##
## REML criterion at convergence: 13841.3
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -6.5860229 -0.6323392 0.0257568 0.6229600 3.2592137
##
## Random effects:
## Groups Name Variance Std.Dev.
## HNDid (Intercept) 0.1870192 0.4324572
## Residual 1.1168455 1.0568091
## Number of obs: 4461, groups: HNDid, 2842
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 2.615956e+00 1.071741e-01 3.156240e+03 24.40848 < 2.22e-16
## Time -2.320545e-02 1.615987e-02 2.472044e+03 -1.43599 0.1511311
## Age0 -1.480275e-02 1.971729e-03 2.719625e+03 -7.50750 8.1208e-14
## SexMen -2.532870e-01 3.632486e-02 2.654729e+03 -6.97283 3.9054e-12
## RaceAfrAm -1.004138e-01 3.699559e-02 2.647237e+03 -2.71421 0.0066865
## PovStatBelow -8.977480e-02 3.699402e-02 2.643340e+03 -2.42674 0.0153017
##
## Correlation of Fixed Effects:
## (Intr) Time Age0 SexMen RcAfrA
## Time -0.310
## Age0 -0.897 0.008
## SexMen -0.164 0.019 0.008
## RaceAfrAm -0.184 -0.025 0.010 -0.008
## PovStatBelw -0.189 0.035 0.066 0.060 -0.152
Digit Span Forward
t-Test
DigitSpanFwd = t.test(widenp13$DigitSpanFwd.1,widenp13$DigitSpanFwd.3,paired=TRUE)
DigitSpanFwd
##
## Paired t-test
##
## data: widenp13$DigitSpanFwd.1 and widenp13$DigitSpanFwd.3
## t = 1.5353205, df = 1748, p-value = 0.1248861
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -0.01760942808 0.14453910218
## sample estimates:
## mean of the differences
## 0.06346483705
Mixed Model Regression
DigitSpanFwd = lmer(DigitSpanFwd~Time + Age0 + Sex + Race + PovStat + (1|HNDid),data=np13_long)
summary(DigitSpanFwd)
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: DigitSpanFwd ~ Time + Age0 + Sex + Race + PovStat + (1 | HNDid)
## Data: np13_long
##
## REML criterion at convergence: 19364
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -2.67121566 -0.46372315 -0.08273055 0.42937660 2.87375169
##
## Random effects:
## Groups Name Variance Std.Dev.
## HNDid (Intercept) 3.152055 1.775403
## Residual 1.494908 1.222664
## Number of obs: 4668, groups: HNDid, 2919
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 8.999731e+00 2.150910e-01 3.069589e+03 41.84150 < 2.22e-16
## Time -2.328120e-02 1.975289e-02 2.072776e+03 -1.17862 0.238684
## Age0 -2.589013e-02 4.104686e-03 2.910082e+03 -6.30746 3.2676e-10
## SexMen 1.453786e-01 7.638145e-02 2.896318e+03 1.90332 0.057097
## RaceAfrAm -6.729177e-01 7.782012e-02 2.895796e+03 -8.64709 < 2.22e-16
## PovStatBelow -5.442575e-01 7.799859e-02 2.900235e+03 -6.97779 3.7007e-12
##
## Correlation of Fixed Effects:
## (Intr) Time Age0 SexMen RcAfrA
## Time -0.171
## Age0 -0.927 0.009
## SexMen -0.168 0.013 0.005
## RaceAfrAm -0.191 -0.030 0.007 -0.011
## PovStatBelw -0.181 0.011 0.059 0.059 -0.152
Digit Span Backward
t-Test
DigitSpanBck = t.test(widenp13$DigitSpanBck.1,widenp13$DigitSpanBck.3,paired=TRUE)
DigitSpanBck
##
## Paired t-test
##
## data: widenp13$DigitSpanBck.1 and widenp13$DigitSpanBck.3
## t = 1.3336342, df = 1724, p-value = 0.1824999
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -0.02619402374 0.13749837157
## sample estimates:
## mean of the differences
## 0.05565217391
Mixed Model Regression
DigitSpanBck = lmer(DigitSpanBck~Time + Age0 + Sex + Race + PovStat + (1|HNDid),data=np13_long)
summary(DigitSpanBck)
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: DigitSpanBck ~ Time + Age0 + Sex + Race + PovStat + (1 | HNDid)
## Data: np13_long
##
## REML criterion at convergence: 19021
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.2574026 -0.4716392 -0.0488628 0.4177069 4.0117754
##
## Random effects:
## Groups Name Variance Std.Dev.
## HNDid (Intercept) 2.857465 1.690404
## Residual 1.510119 1.228869
## Number of obs: 4629, groups: HNDid, 2904
##
## Fixed effects:
## Estimate Std. Error df t value
## (Intercept) 7.793080e+00 2.082415e-01 3.046828e+03 37.42329
## Time -3.356641e-02 1.990115e-02 2.059459e+03 -1.68666
## Age0 -2.782140e-02 3.972023e-03 2.877139e+03 -7.00434
## SexMen -9.652966e-02 7.393541e-02 2.862136e+03 -1.30559
## RaceAfrAm -1.052518e+00 7.533006e-02 2.860699e+03 -13.97209
## PovStatBelow -5.861208e-01 7.553269e-02 2.867545e+03 -7.75983
## Pr(>|t|)
## (Intercept) < 2.22e-16
## Time 0.091821
## Age0 3.0773e-12
## SexMen 0.191795
## RaceAfrAm < 2.22e-16
## PovStatBelow 1.1736e-14
##
## Correlation of Fixed Effects:
## (Intr) Time Age0 SexMen RcAfrA
## Time -0.178
## Age0 -0.926 0.009
## SexMen -0.166 0.014 0.004
## RaceAfrAm -0.190 -0.033 0.007 -0.012
## PovStatBelw -0.179 0.010 0.057 0.060 -0.153
Trail Making Test Part A
t-Test
TrailsA = t.test(widenp13$TrailsAtestSec.1,widenp13$TrailsAtestSec.3,paired=TRUE)
TrailsA
##
## Paired t-test
##
## data: widenp13$TrailsAtestSec.1 and widenp13$TrailsAtestSec.3
## t = -2.1177042, df = 1957, p-value = 0.03432592
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -5.7094000021 -0.2190984657
## sample estimates:
## mean of the differences
## -2.964249234
Mixed Model Regression
TrailsA = lmer(TrailsAtestSec~Time + Age0 + Sex + Race + PovStat + (1|HNDid),data=np13_long)
summary(TrailsA)
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: TrailsAtestSec ~ Time + Age0 + Sex + Race + PovStat + (1 | HNDid)
## Data: np13_long
##
## REML criterion at convergence: 52966.3
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -2.2432031 -0.2326372 -0.1158938 0.0301708 9.9749310
##
## Random effects:
## Groups Name Variance Std.Dev.
## HNDid (Intercept) 503.071 22.42924
## Residual 2387.247 48.85946
## Number of obs: 4908, groups: HNDid, 2950
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) -5.04015364 4.81588492 2586.05075735 -1.04657 0.29539643
## Time 0.93456021 0.71383607 1877.98422035 1.30921 0.19062391
## Age0 0.70791573 0.08940737 2114.05816193 7.91787 3.8671e-15
## SexMen 6.03048099 1.65462979 2064.70242660 3.64461 0.00027441
## RaceAfrAm 9.77131535 1.68328951 2049.59840521 5.80489 7.4461e-09
## PovStatBelow 6.32609283 1.68998192 2075.88088326 3.74329 0.00018656
##
## Correlation of Fixed Effects:
## (Intr) Time Age0 SexMen RcAfrA
## Time -0.287
## Age0 -0.904 0.010
## SexMen -0.166 0.022 0.008
## RaceAfrAm -0.181 -0.036 0.009 -0.011
## PovStatBelw -0.177 0.009 0.062 0.057 -0.151
Trail Making Test Part B
t-Test
TrailsB = t.test(widenp13$TrailsBtestSec.1,widenp13$TrailsBtestSec.3,paired=TRUE)
TrailsB
##
## Paired t-test
##
## data: widenp13$TrailsBtestSec.1 and widenp13$TrailsBtestSec.3
## t = -5.8736656, df = 1947, p-value = 5.000876e-09
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -25.41862850 -12.69328115
## sample estimates:
## mean of the differences
## -19.05595483
Mixed Model Regression
TrailsB = lmer(TrailsBtestSec~Time + Age0 + Sex + Race + PovStat + (1|HNDid),data=np13_long)
summary(TrailsB)
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: TrailsBtestSec ~ Time + Age0 + Sex + Race + PovStat + (1 | HNDid)
## Data: np13_long
##
## REML criterion at convergence: 62949.1
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -2.6246228 -0.3203912 -0.1421073 0.0885997 3.2701004
##
## Random effects:
## Groups Name Variance Std.Dev.
## HNDid (Intercept) 17423.97 131.9999
## Residual 10454.11 102.2454
## Number of obs: 4891, groups: HNDid, 2943
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) -110.0986793 16.3966298 3062.6080313 -6.71471 2.2370e-11
## Time 9.1535400 1.5701753 2202.5731956 5.82963 6.3728e-09
## Age0 4.0418352 0.3122089 2873.7324045 12.94593 < 2.22e-16
## SexMen 18.7267366 5.8001135 2847.8042622 3.22868 0.0012577
## RaceAfrAm 69.6363387 5.9051771 2840.6318987 11.79242 < 2.22e-16
## PovStatBelow 51.8487481 5.9204939 2851.4427268 8.75750 < 2.22e-16
##
## Correlation of Fixed Effects:
## (Intr) Time Age0 SexMen RcAfrA
## Time -0.183
## Age0 -0.925 0.008
## SexMen -0.169 0.017 0.008
## RaceAfrAm -0.190 -0.028 0.008 -0.013
## PovStatBelw -0.179 0.006 0.059 0.061 -0.154
Word Fluency
t-Test
FluencyWord = t.test(widenp13$FluencyWord.1,widenp13$FluencyWord.3,paired=TRUE)
FluencyWord
##
## Paired t-test
##
## data: widenp13$FluencyWord.1 and widenp13$FluencyWord.3
## t = -1.2563914, df = 1980, p-value = 0.2091223
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -0.30509032753 0.06682682425
## sample estimates:
## mean of the differences
## -0.1191317516
Mixed Model Regression
FluencyWord = lmer(FluencyWord~Time + Age0 + Sex + Race + PovStat + (1|HNDid),data=np13_long)
summary(FluencyWord)
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: FluencyWord ~ Time + Age0 + Sex + Race + PovStat + (1 | HNDid)
## Data: np13_long
##
## REML criterion at convergence: 29113.5
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.3402004 -0.5012955 -0.0305745 0.4485452 2.7936286
##
## Random effects:
## Groups Name Variance Std.Dev.
## HNDid (Intercept) 18.013372 4.244216
## Residual 8.895295 2.982498
## Number of obs: 4939, groups: HNDid, 2958
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 2.409721e+01 5.111920e-01 3.131757e+03 47.13925 < 2.22e-16
## Time 7.806695e-02 4.569525e-02 2.270765e+03 1.70843 0.08769398
## Age0 -8.993507e-02 9.755877e-03 2.967980e+03 -9.21855 < 2.22e-16
## SexMen 6.871435e-01 1.812067e-01 2.943420e+03 3.79204 0.00015241
## RaceAfrAm -1.703338e+00 1.845301e-01 2.941549e+03 -9.23068 < 2.22e-16
## PovStatBelow -1.342639e+00 1.850196e-01 2.949998e+03 -7.25674 5.0461e-13
##
## Correlation of Fixed Effects:
## (Intr) Time Age0 SexMen RcAfrA
## Time -0.170
## Age0 -0.927 0.006
## SexMen -0.168 0.015 0.006
## RaceAfrAm -0.192 -0.026 0.009 -0.012
## PovStatBelw -0.176 0.003 0.056 0.060 -0.154