Trails B Regression Model 1
## Loading required package: Matrix
## KernSmooth 2.23 loaded
## Copyright M. P. Wand 1997-2009
##
## Attaching package: 'lmerTest'
##
## The following object is masked from 'package:lme4':
##
## lmer
##
## The following object is masked from 'package:stats':
##
## step
## Warning: number of observations <= rank(Z); variance-covariance matrix
## will be unidentifiable
## Linear mixed model fit by maximum likelihood ['merModLmerTest']
## Formula: TrailsBtestSec ~ (Age + IPVstatus + Sex + Race)^4 + (Age | HNDid) + (1 | subclass)
## Data: IPVandCognitionDataSet2
## AIC BIC logLik deviance
## 1593.3 1652.8 -775.6 1551.3
## Random effects:
## Groups Name Std.Dev. Corr
## HNDid (Intercept) 1.38e+02
## Age 5.75e+00 1.00
## subclass (Intercept) 4.47e-04
## Residual 8.07e+01
## Number of obs: 126, groups: HNDid, 63; subclass, 21
## Fixed Effects:
## (Intercept) Age
## 58.88 -1.10
## IPVstatus1 SexMen
## 12.33 7.09
## RaceAfrAm Age:IPVstatus1
## 143.98 1.71
## Age:SexMen Age:RaceAfrAm
## 2.19 3.64
## IPVstatus1:SexMen IPVstatus1:RaceAfrAm
## 265.76 -129.99
## SexMen:RaceAfrAm Age:IPVstatus1:SexMen
## -33.56 15.20
## Age:IPVstatus1:RaceAfrAm Age:SexMen:RaceAfrAm
## -2.13 3.66
## IPVstatus1:SexMen:RaceAfrAm Age:IPVstatus1:SexMen:RaceAfrAm
## -54.47 -30.19
## Warning: number of observations <= rank(Z); variance-covariance matrix will be unidentifiable
## Warning:
## model has been refitted with REML=TRUE
##
## Warning: number of observations <= rank(Z); variance-covariance matrix will be unidentifiable
## Warning: number of observations <= rank(Z); variance-covariance matrix will be unidentifiable
## Random term (Age | HNDid) was eliminated because of having correlation +-1 or NaN
## Warning: number of observations <= rank(Z); variance-covariance matrix
## will be unidentifiable
## Random term (Age + 0 | HNDid) was eliminated because of standard deviation being equal to 0
##
## Random effects:
## Chi.sq Chi.DF elim.num p.value
## (1 | subclass) 0.16 1 1 0.6926
## (1 | HNDid) 22.90 1 kept 0
##
## Fixed effects:
## Sum Sq Mean Sq NumDF DenDF F.value elim.num
## Age:IPVstatus:Sex:Race 19558.4 19558.4 1 105.41 2.4345 1
## Age:IPVstatus:Sex 195.7 195.7 1 107.34 0.0004 2
## IPVstatus:Sex:Race 3775.9 3775.9 1 50.71 0.4286 3
## Age:Sex:Race 4500.9 4500.9 1 112.16 0.5128 4
## Sex:Race 326.4 326.4 1 53.76 0.0025 5
## Age:Sex 8788.2 8788.2 1 112.86 1.1693 6
## Age:IPVstatus:Race 28895.6 28895.6 1 112.79 3.1126 7
## Age:Race 4960.6 4960.6 1 116.65 0.0799 8
## Age:IPVstatus 2915.2 2915.2 1 114.64 0.1289 9
## IPVstatus:Race 5422.8 5422.8 1 55.55 0.7921 10
## Age 31578.2 31578.2 1 117.78 3.1626 11
## IPVstatus 11700.0 11700.0 1 58.00 2.3081 kept
## Sex 16971.7 16971.7 1 58.00 7.0216 kept
## Race 43011.2 43011.2 1 58.00 4.3014 kept
## IPVstatus:Sex 86778.8 86778.8 1 58.00 10.2288 kept
## Pr(>F)
## Age:IPVstatus:Sex:Race 0.1217
## Age:IPVstatus:Sex 0.9848
## IPVstatus:Sex:Race 0.5156
## Age:Sex:Race 0.4754
## Sex:Race 0.9599
## Age:Sex 0.2818
## Age:IPVstatus:Race 0.0804
## Age:Race 0.7779
## Age:IPVstatus 0.7203
## IPVstatus:Race 0.3773
## Age 0.0779
## IPVstatus 0.1341
## Sex 0.0104
## Race 0.0425
## IPVstatus:Sex 0.0022
##
## Least squares means:
## IPVstatus Sex Race Estimate Standard Error DF
## IPVstatus 0 1 NA NA 113.7 21.3 58
## IPVstatus 1 2 NA NA 167.9 29.4 58
## Sex Women NA 2 NA 93.6 25.2 58
## Sex Men NA 1 NA 188.0 26.2 58
## Race White NA NA 2 104.7 28.5 58
## Race AfrAm NA NA 1 176.9 21.8 58
## IPVstatus:Sex 0 Women 1 2 NA 123.8 32.1 58
## IPVstatus:Sex 1 Women 2 2 NA 63.3 38.2 58
## IPVstatus:Sex 0 Men 1 1 NA 103.6 27.1 58
## IPVstatus:Sex 1 Men 2 1 NA 272.5 44.4 58
## t-value Lower CI Upper CI p-value
## IPVstatus 0 5.35 71.2 156 <2e-16
## IPVstatus 1 5.71 109.0 227 <2e-16
## Sex Women 3.72 43.2 144 0.0005
## Sex Men 7.19 135.7 240 <2e-16
## Race White 3.67 47.6 162 0.0005
## Race AfrAm 8.11 133.3 221 <2e-16
## IPVstatus:Sex 0 Women 3.86 59.6 188 0.0003
## IPVstatus:Sex 1 Women 1.66 -13.2 140 0.1030
## IPVstatus:Sex 0 Men 3.82 49.4 158 0.0003
## IPVstatus:Sex 1 Men 6.14 183.6 361 <2e-16
##
## Differences of LSMEANS:
## Estimate Standard Error DF t-value
## IPVstatus 0-1 -54.2 35.7 58.0 -1.52
## Sex Women-Men -94.5 35.7 58.0 -2.65
## Race White-AfrAm -72.2 34.8 58.0 -2.07
## IPVstatus:Sex 0 Women- 1 Women 60.5 49.4 58.0 1.22
## IPVstatus:Sex 0 Women- 0 Men 20.2 41.4 58.0 0.49
## IPVstatus:Sex 0 Women- 1 Men -148.7 53.9 58.0 -2.76
## IPVstatus:Sex 1 Women- 0 Men -40.3 46.7 58.0 -0.86
## IPVstatus:Sex 1 Women- 1 Men -209.1 58.3 58.0 -3.59
## IPVstatus:Sex 0 Men- 1 Men -168.8 51.7 58.0 -3.27
## Lower CI Upper CI p-value
## IPVstatus 0-1 -125.5 17.20 0.134
## Sex Women-Men -165.9 -23.11 0.010
## Race White-AfrAm -142.0 -2.52 0.043
## IPVstatus:Sex 0 Women- 1 Women -38.4 159.44 0.226
## IPVstatus:Sex 0 Women- 0 Men -62.8 103.13 0.628
## IPVstatus:Sex 0 Women- 1 Men -256.6 -40.72 0.008
## IPVstatus:Sex 1 Women- 0 Men -133.7 53.10 0.391
## IPVstatus:Sex 1 Women- 1 Men -325.8 -92.49 7e-04
## IPVstatus:Sex 0 Men- 1 Men -272.3 -65.40 0.002
##
## Final model:
## lme4::lmer(formula = TrailsBtestSec ~ IPVstatus + Sex + Race +
## (1 | HNDid) + IPVstatus:Sex, data = IPVandCognitionDataSet2,
## REML = reml, contrasts = l)
Re-run the suggested final Model 1
(mm1 = lmer(TrailsBtestSec ~ IPVstatus + Sex + Race + (1 | HNDid) + IPVstatus:Sex,
data = IPVandCognitionDataSet2, REML = F))
## Linear mixed model fit by maximum likelihood ['merModLmerTest']
## Formula: TrailsBtestSec ~ IPVstatus + Sex + Race + (1 | HNDid) + IPVstatus:Sex
## Data: IPVandCognitionDataSet2
## AIC BIC logLik deviance
## 1587.4 1607.2 -786.7 1573.4
## Random effects:
## Groups Name Std.Dev.
## HNDid (Intercept) 110.9
## Residual 86.6
## Number of obs: 126, groups: HNDid, 63
## Fixed Effects:
## (Intercept) IPVstatus1 SexMen
## 87.7 -60.5 -20.2
## RaceAfrAm IPVstatus1:SexMen
## 72.2 229.3
summary(mm1)
## Linear mixed model fit by maximum likelihood ['merModLmerTest']
## Formula: TrailsBtestSec ~ IPVstatus + Sex + Race + (1 | HNDid) + IPVstatus:Sex
## Data: IPVandCognitionDataSet2
##
## AIC BIC logLik deviance
## 1587.4 1607.2 -786.7 1573.4
##
## Random effects:
## Groups Name Variance Std.Dev.
## HNDid (Intercept) 12290 110.9
## Residual 7500 86.6
## Number of obs: 126, groups: HNDid, 63
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 87.7 38.4 63.0 2.28 0.0257
## IPVstatus1 -60.5 47.4 63.0 -1.28 0.2068
## SexMen -20.2 39.8 63.0 -0.51 0.6135
## RaceAfrAm 72.2 33.4 63.0 2.16 0.0345
## IPVstatus1:SexMen 229.3 68.8 63.0 3.33 0.0014
##
## Correlation of Fixed Effects:
## (Intr) IPVst1 SexMen RcAfrA
## IPVstatus1 -0.551
## SexMen -0.657 0.484
## RaceAfrAm -0.629 0.098 0.117
## IPVstts1:SM 0.405 -0.693 -0.583 -0.108
plot(st)
plot(mm1)
Trails B Regression Model 2 (with CES)
load("~/Desktop/Megan/Research/IPV and Cognition Paper/IPV R Output/IPVandCognitionDataSet2.rda")
library(lme4)
library(lmerTest)
(mm2 = lmer(TrailsBtestSec ~ (Age + IPVstatus + Sex + Race + CES1)^5 + (Age |
HNDid) + (1 | subclass), data = IPVandCognitionDataSet2, REML = F))
## Warning: number of observations <= rank(Z); variance-covariance matrix
## will be unidentifiable
## Linear mixed model fit by maximum likelihood ['merModLmerTest']
## Formula: TrailsBtestSec ~ (Age + IPVstatus + Sex + Race + CES1)^5 + (Age | HNDid) + (1 | subclass)
## Data: IPVandCognitionDataSet2
## AIC BIC logLik deviance
## 1604.5 1709.4 -765.2 1530.5
## Random effects:
## Groups Name Std.Dev. Corr
## HNDid (Intercept) 1.52e+02
## Age 8.02e+00 1.00
## subclass (Intercept) 4.13e-04
## Residual 7.16e+01
## Number of obs: 126, groups: HNDid, 63; subclass, 21
## Fixed Effects:
## (Intercept)
## 57.39
## Age
## -2.48
## IPVstatus1
## 48.61
## SexMen
## 7.22
## RaceAfrAm
## 253.83
## CES11
## 6.61
## Age:IPVstatus1
## 6.82
## Age:SexMen
## 4.05
## Age:RaceAfrAm
## 9.49
## Age:CES11
## 3.15
## IPVstatus1:SexMen
## 313.79
## IPVstatus1:RaceAfrAm
## -282.39
## IPVstatus1:CES11
## -51.03
## SexMen:RaceAfrAm
## -162.08
## SexMen:CES11
## -8.85
## RaceAfrAm:CES11
## -284.96
## Age:IPVstatus1:SexMen
## 12.80
## Age:IPVstatus1:RaceAfrAm
## -12.74
## Age:IPVstatus1:CES11
## -7.96
## Age:SexMen:RaceAfrAm
## -6.08
## Age:SexMen:CES11
## -5.41
## Age:RaceAfrAm:CES11
## -16.46
## IPVstatus1:SexMen:RaceAfrAm
## 276.63
## IPVstatus1:SexMen:CES11
## -244.75
## IPVstatus1:RaceAfrAm:CES11
## 340.28
## SexMen:RaceAfrAm:CES11
## 353.26
## Age:IPVstatus1:SexMen:RaceAfrAm
## -11.85
## Age:IPVstatus1:SexMen:CES11
## -3.96
## Age:IPVstatus1:RaceAfrAm:CES11
## 24.19
## Age:SexMen:RaceAfrAm:CES11
## 29.54
## IPVstatus1:SexMen:RaceAfrAm:CES11
## -308.77
## Age:IPVstatus1:SexMen:RaceAfrAm:CES11
## -12.12
(st = step(mm2))
## Warning: number of observations <= rank(Z); variance-covariance matrix will be unidentifiable
## Warning:
## model has been refitted with REML=TRUE
##
## Warning: number of observations <= rank(Z); variance-covariance matrix will be unidentifiable
## Warning: number of observations <= rank(Z); variance-covariance matrix will be unidentifiable
## Random term (Age | HNDid) was eliminated because of having correlation +-1 or NaN
## Warning: number of observations <= rank(Z); variance-covariance matrix
## will be unidentifiable
## Random term (Age + 0 | HNDid) was eliminated because of standard deviation being equal to 0
##
## Random effects:
## Chi.sq Chi.DF elim.num p.value
## (1 | subclass) 1.24 1 1 0.2651
## (1 | HNDid) 22.47 1 kept 0
##
## Fixed effects:
## Sum Sq Mean Sq NumDF DenDF F.value
## Age:IPVstatus:Sex:Race:CES1 63.14 63.14 1 57.95 0.0079
## IPVstatus:Sex:Race:CES1 347.43 347.43 1 68.04 0.0432
## Age:IPVstatus:Sex:CES1 818.83 818.83 1 78.81 0.0514
## Age:IPVstatus:Race:CES1 439.44 439.44 1 69.70 0.2747
## IPVstatus:Race:CES1 13.43 13.43 1 46.96 0.0205
## Age:IPVstatus:CES1 149.86 149.86 1 98.07 0.1060
## Age:Sex:Race:CES1 4852.41 4852.41 1 89.36 0.5278
## Sex:Race:CES1 644.29 644.29 1 43.86 0.0169
## Age:Race:CES1 6738.35 6738.35 1 94.36 0.1479
## Race:CES1 3410.84 3410.84 1 43.57 0.1866
## Age:Sex:CES1 14181.27 14181.27 1 101.42 0.8507
## Age:CES1 1511.08 1511.08 1 99.63 0.0191
## Age:IPVstatus:Sex:Race 5518.30 5518.30 1 101.66 1.0752
## Age:IPVstatus:Sex 817.54 817.54 1 103.83 0.0783
## Age:Sex:Race 3842.65 3842.65 1 105.92 0.1341
## Age:IPVstatus:Race 13342.77 13342.77 1 104.31 1.7518
## Age:Race 1681.41 1681.41 1 108.65 0.0525
## Age:IPVstatus 3800.90 3800.90 1 107.29 0.7436
## Age:Sex 7563.29 7563.29 1 108.50 2.6278
## IPVstatus:Sex:Race 7153.81 7153.81 1 51.02 2.4372
## IPVstatus:Race 5383.60 5383.60 1 50.55 0.0455
## Sex:Race 283.52 283.52 1 51.79 0.1028
## Age 31568.72 31568.72 1 113.72 3.0769
## IPVstatus 9776.43 9776.43 1 54.00 4.2566
## Sex 13945.77 13945.77 1 54.00 10.7327
## Race 35248.46 35248.46 1 54.00 7.1110
## CES1 5814.43 5814.43 1 54.00 2.9137
## IPVstatus:Sex 75603.35 75603.35 1 54.00 12.2851
## IPVstatus:CES1 6267.46 6267.46 1 54.00 0.6724
## Sex:CES1 860.00 860.00 1 54.00 1.3924
## IPVstatus:Sex:CES1 28790.92 28790.92 1 54.00 4.8698
## elim.num Pr(>F)
## Age:IPVstatus:Sex:Race:CES1 1 0.9293
## IPVstatus:Sex:Race:CES1 2 0.8360
## Age:IPVstatus:Sex:CES1 3 0.8213
## Age:IPVstatus:Race:CES1 4 0.6018
## IPVstatus:Race:CES1 5 0.8868
## Age:IPVstatus:CES1 6 0.7454
## Age:Sex:Race:CES1 7 0.4694
## Sex:Race:CES1 8 0.8973
## Age:Race:CES1 9 0.7014
## Race:CES1 10 0.6679
## Age:Sex:CES1 11 0.3585
## Age:CES1 12 0.8904
## Age:IPVstatus:Sex:Race 13 0.3022
## Age:IPVstatus:Sex 14 0.7801
## Age:Sex:Race 15 0.7149
## Age:IPVstatus:Race 16 0.1885
## Age:Race 17 0.8192
## Age:IPVstatus 18 0.3904
## Age:Sex 19 0.1079
## IPVstatus:Sex:Race 20 0.1247
## IPVstatus:Race 21 0.8319
## Sex:Race 22 0.7498
## Age 23 0.0821
## IPVstatus kept 0.0439
## Sex kept 0.0018
## Race kept 0.0101
## CES1 kept 0.0936
## IPVstatus:Sex kept 0.0009
## IPVstatus:CES1 kept 0.4158
## Sex:CES1 kept 0.2432
## IPVstatus:Sex:CES1 kept 0.0316
##
## Least squares means:
## IPVstatus Sex Race CES1 Estimate
## IPVstatus 0 1 NA NA NA 106.9
## IPVstatus 1 2 NA NA NA 181.8
## Sex Women NA 2 NA NA 84.8
## Sex Men NA 1 NA NA 204.0
## Race White NA NA 2 NA 97.1
## Race AfrAm NA NA 1 NA 191.6
## CES1 0 NA NA NA 1 175.4
## CES1 1 NA NA NA 2 113.3
## IPVstatus:Sex 0 Women 1 2 NA NA 110.9
## IPVstatus:Sex 1 Women 2 2 NA NA 58.6
## IPVstatus:Sex 0 Men 1 1 NA NA 102.9
## IPVstatus:Sex 1 Men 2 1 NA NA 305.0
## IPVstatus:CES1 0 0 1 NA NA 1 123.1
## IPVstatus:CES1 1 0 2 NA NA 1 227.8
## IPVstatus:CES1 0 1 1 NA NA 2 90.7
## IPVstatus:CES1 1 1 2 NA NA 2 135.9
## Sex:CES1 Women 0 NA 2 NA 1 94.2
## Sex:CES1 Men 0 NA 1 NA 1 256.7
## Sex:CES1 Women 1 NA 2 NA 2 75.4
## Sex:CES1 Men 1 NA 1 NA 2 151.2
## IPVstatus:Sex:CES1 0 Women 0 1 2 NA 1 146.7
## IPVstatus:Sex:CES1 1 Women 0 2 2 NA 1 41.6
## IPVstatus:Sex:CES1 0 Men 0 1 1 NA 1 99.6
## IPVstatus:Sex:CES1 1 Men 0 2 1 NA 1 413.9
## IPVstatus:Sex:CES1 0 Women 1 1 2 NA 2 75.2
## IPVstatus:Sex:CES1 1 Women 1 2 2 NA 2 75.6
## IPVstatus:Sex:CES1 0 Men 1 1 1 NA 2 106.2
## IPVstatus:Sex:CES1 1 Men 1 2 1 NA 2 196.2
## Standard Error DF t-value Lower CI Upper CI
## IPVstatus 0 21.8 54 4.91 63.25 151
## IPVstatus 1 29.8 54 6.10 122.10 242
## Sex Women 25.3 54 3.35 34.06 135
## Sex Men 26.9 54 7.58 150.02 258
## Race White 28.9 54 3.36 39.21 155
## Race AfrAm 22.3 54 8.60 146.97 236
## CES1 0 26.9 54 6.53 121.58 229
## CES1 1 25.4 54 4.47 62.44 164
## IPVstatus:Sex 0 Women 32.4 54 3.43 46.02 176
## IPVstatus:Sex 1 Women 38.0 54 1.54 -17.47 135
## IPVstatus:Sex 0 Men 28.1 54 3.66 46.52 159
## IPVstatus:Sex 1 Men 45.7 54 6.68 213.47 397
## IPVstatus:CES1 0 0 25.5 54 4.83 72.01 174
## IPVstatus:CES1 1 0 47.1 54 4.83 133.29 322
## IPVstatus:CES1 0 1 34.4 54 2.63 21.64 160
## IPVstatus:CES1 1 1 36.2 54 3.76 63.39 208
## Sex:CES1 Women 0 35.6 54 2.64 22.75 166
## Sex:CES1 Men 0 40.6 54 6.32 175.35 338
## Sex:CES1 Women 1 34.8 54 2.17 5.58 145
## Sex:CES1 Men 1 35.7 54 4.23 79.51 223
## IPVstatus:Sex:CES1 0 Women 0 39.2 54 3.74 68.13 225
## IPVstatus:Sex:CES1 1 Women 0 58.6 54 0.71 -75.88 159
## IPVstatus:Sex:CES1 0 Men 0 32.3 54 3.08 34.80 164
## IPVstatus:Sex:CES1 1 Men 0 74.7 54 5.54 264.23 564
## IPVstatus:Sex:CES1 0 Women 1 50.3 54 1.49 -25.75 176
## IPVstatus:Sex:CES1 1 Women 1 48.8 54 1.55 -22.21 173
## IPVstatus:Sex:CES1 0 Men 1 45.8 54 2.32 14.38 198
## IPVstatus:Sex:CES1 1 Men 1 53.9 54 3.64 88.03 304
## p-value
## IPVstatus 0 <2e-16
## IPVstatus 1 <2e-16
## Sex Women 0.0015
## Sex Men <2e-16
## Race White 0.0014
## Race AfrAm <2e-16
## CES1 0 <2e-16
## CES1 1 <2e-16
## IPVstatus:Sex 0 Women 0.0012
## IPVstatus:Sex 1 Women 0.1283
## IPVstatus:Sex 0 Men 0.0006
## IPVstatus:Sex 1 Men <2e-16
## IPVstatus:CES1 0 0 <2e-16
## IPVstatus:CES1 1 0 <2e-16
## IPVstatus:CES1 0 1 0.0110
## IPVstatus:CES1 1 1 0.0004
## Sex:CES1 Women 0 0.0107
## Sex:CES1 Men 0 <2e-16
## Sex:CES1 Women 1 0.0348
## Sex:CES1 Men 1 0.0001
## IPVstatus:Sex:CES1 0 Women 0 0.0004
## IPVstatus:Sex:CES1 1 Women 0 0.4805
## IPVstatus:Sex:CES1 0 Men 0 0.0032
## IPVstatus:Sex:CES1 1 Men 0 <2e-16
## IPVstatus:Sex:CES1 0 Women 1 0.1412
## IPVstatus:Sex:CES1 1 Women 1 0.1271
## IPVstatus:Sex:CES1 0 Men 1 0.0242
## IPVstatus:Sex:CES1 1 Men 1 0.0006
##
## Differences of LSMEANS:
## Estimate Standard Error DF t-value
## IPVstatus 0-1 -74.9 36.32 54.0 -2.06
## Sex Women-Men -119.2 36.38 54.0 -3.28
## Race White-AfrAm -94.5 35.44 54.0 -2.67
## CES1 0-1 62.2 36.42 54.0 1.71
## IPVstatus:Sex 0 Women- 1 Women 52.3 49.17 54.0 1.06
## IPVstatus:Sex 0 Women- 0 Men 8.0 42.18 54.0 0.19
## IPVstatus:Sex 0 Women- 1 Men -194.1 55.52 54.0 -3.50
## IPVstatus:Sex 1 Women- 0 Men -44.2 46.95 54.0 -0.94
## IPVstatus:Sex 1 Women- 1 Men -246.4 59.18 54.0 -4.16
## IPVstatus:Sex 0 Men- 1 Men -202.2 53.44 54.0 -3.78
## IPVstatus:CES1 0 0- 1 0 -104.7 53.43 54.0 -1.96
## IPVstatus:CES1 0 0- 0 1 32.4 42.13 54.0 0.77
## IPVstatus:CES1 0 0- 1 1 -12.8 43.87 54.0 -0.29
## IPVstatus:CES1 1 0- 0 1 137.1 58.02 54.0 2.36
## IPVstatus:CES1 1 0- 1 1 91.9 59.22 54.0 1.55
## IPVstatus:CES1 0 1- 1 1 -45.2 49.13 54.0 -0.92
## Sex:CES1 Women 0- Men 0 -162.6 54.27 54.0 -3.00
## Sex:CES1 Women 0- Women 1 18.8 49.02 54.0 0.38
## Sex:CES1 Women 0- Men 1 -57.0 49.20 54.0 -1.16
## Sex:CES1 Men 0- Women 1 181.3 53.66 54.0 3.38
## Sex:CES1 Men 0- Men 1 105.6 54.36 54.0 1.94
## Sex:CES1 Women 1- Men 1 -75.8 49.07 54.0 -1.54
## Lower CI Upper CI p-value
## IPVstatus 0-1 -147.76 -2.12 0.044
## Sex Women-Men -192.12 -46.25 0.002
## Race White-AfrAm -165.57 -23.45 0.010
## CES1 0-1 -10.85 135.18 0.094
## IPVstatus:Sex 0 Women- 1 Women -46.29 150.87 0.292
## IPVstatus:Sex 0 Women- 0 Men -76.53 92.62 0.850
## IPVstatus:Sex 0 Women- 1 Men -305.43 -82.82 0.001
## IPVstatus:Sex 1 Women- 0 Men -138.37 49.87 0.350
## IPVstatus:Sex 1 Women- 1 Men -365.07 -127.76 1e-04
## IPVstatus:Sex 0 Men- 1 Men -309.32 -95.02 4e-04
## IPVstatus:CES1 0 0- 1 0 -211.79 2.44 0.055
## IPVstatus:CES1 0 0- 0 1 -52.05 116.90 0.445
## IPVstatus:CES1 0 0- 1 1 -100.73 75.18 0.772
## IPVstatus:CES1 1 0- 0 1 20.77 253.43 0.022
## IPVstatus:CES1 1 0- 1 1 -26.83 210.62 0.127
## IPVstatus:CES1 0 1- 1 1 -143.71 53.30 0.362
## Sex:CES1 Women 0- Men 0 -271.38 -53.79 0.004
## Sex:CES1 Women 0- Women 1 -79.51 117.03 0.703
## Sex:CES1 Women 0- Men 1 -155.66 41.61 0.252
## Sex:CES1 Men 0- Women 1 73.77 288.93 0.001
## Sex:CES1 Men 0- Men 1 -3.43 214.56 0.057
## Sex:CES1 Women 1- Men 1 -174.17 22.60 0.128
##
## Final model:
## lme4::lmer(formula = TrailsBtestSec ~ IPVstatus + Sex + Race +
## CES1 + (1 | HNDid) + IPVstatus:Sex + IPVstatus:CES1 + Sex:CES1 +
## IPVstatus:Sex:CES1, data = IPVandCognitionDataSet2, REML = reml,
## contrasts = l)
Re-run the suggested final Model 2
(mm2 = lmer(TrailsBtestSec ~ IPVstatus + Sex + Race + CES1 + (1 | HNDid) + IPVstatus:Sex +
IPVstatus:CES1 + Sex:CES1 + IPVstatus:Sex:CES1, data = IPVandCognitionDataSet2,
REML = F))
## Linear mixed model fit by maximum likelihood ['merModLmerTest']
## Formula: TrailsBtestSec ~ IPVstatus + Sex + Race + CES1 + (1 | HNDid) + IPVstatus:Sex + IPVstatus:CES1 + Sex:CES1 + IPVstatus:Sex:CES1
## Data: IPVandCognitionDataSet2
## AIC BIC logLik deviance
## 1588 1619 -783 1566
## Random effects:
## Groups Name Std.Dev.
## HNDid (Intercept) 102.4
## Residual 86.6
## Number of obs: 126, groups: HNDid, 63
## Fixed Effects:
## (Intercept) IPVstatus1 SexMen
## 99.4 -105.0 -47.1
## RaceAfrAm CES11 IPVstatus1:SexMen
## 94.5 -71.5 419.4
## IPVstatus1:CES11 SexMen:CES11 IPVstatus1:SexMen:CES11
## 105.4 78.1 -329.8
summary(mm2)
## Linear mixed model fit by maximum likelihood ['merModLmerTest']
## Formula: TrailsBtestSec ~ IPVstatus + Sex + Race + CES1 + (1 | HNDid) + IPVstatus:Sex + IPVstatus:CES1 + Sex:CES1 + IPVstatus:Sex:CES1
## Data: IPVandCognitionDataSet2
##
## AIC BIC logLik deviance
## 1588 1619 -783 1566
##
## Random effects:
## Groups Name Variance Std.Dev.
## HNDid (Intercept) 10494 102.4
## Residual 7500 86.6
## Number of obs: 126, groups: HNDid, 63
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 99.4 41.6 63.0 2.39 0.0199
## IPVstatus1 -105.0 64.6 63.0 -1.63 0.1090
## SexMen -47.1 46.8 63.0 -1.01 0.3182
## RaceAfrAm 94.5 32.8 63.0 2.88 0.0054
## CES11 -71.5 58.2 63.0 -1.23 0.2236
## IPVstatus1:SexMen 419.4 99.7 63.0 4.20 8.4e-05
## IPVstatus1:CES11 105.4 92.7 63.0 1.14 0.2596
## SexMen:CES11 78.1 77.6 63.0 1.01 0.3182
## IPVstatus1:SexMen:CES11 -329.8 138.4 63.0 -2.38 0.0202
##
## Correlation of Fixed Effects:
## (Intr) IPVst1 SexMen RcAfrA CES11 IPVs1:SM IPV1:C SM:CES
## IPVstatus1 -0.440
## SexMen -0.691 0.424
## RaceAfrAm -0.502 -0.083 0.052
## CES11 -0.473 0.355 0.469 -0.125
## IPVstts1:SM 0.247 -0.654 -0.461 0.129 -0.239
## IPVs1:CES11 0.231 -0.710 -0.288 0.210 -0.644 0.475
## SexMn:CES11 0.367 -0.264 -0.598 0.067 -0.746 0.291 0.477
## IPV1:SM:CES -0.102 0.484 0.325 -0.244 0.444 -0.740 -0.692 -0.575
plot(st)
plot(mm2)
