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: TrailsBlow ~ (Age + IPVstatus + Sex + Race)^4 + (Age | HNDid) + (1 | subclass)
## Data: IPVandCognitionDataSet2
## AIC BIC logLik deviance
## 1404.1 1463.7 -681.1 1362.1
## Random effects:
## Groups Name Std.Dev. Corr
## HNDid (Intercept) 73.16
## Age 2.52 1.00
## subclass (Intercept) 0.00
## Residual 34.74
## Number of obs: 126, groups: HNDid, 63; subclass, 21
## Fixed Effects:
## (Intercept) Age
## 76.0386 1.1322
## IPVstatus1 SexMen
## 0.4245 18.5488
## RaceAfrAm Age:IPVstatus1
## 71.9467 0.0807
## Age:SexMen Age:RaceAfrAm
## 1.9750 1.5792
## IPVstatus1:SexMen IPVstatus1:RaceAfrAm
## 92.2718 -65.3061
## SexMen:RaceAfrAm Age:IPVstatus1:SexMen
## -34.3284 3.9561
## Age:IPVstatus1:RaceAfrAm Age:SexMen:RaceAfrAm
## -0.9871 -1.2101
## IPVstatus1:SexMen:RaceAfrAm Age:IPVstatus1:SexMen:RaceAfrAm
## 19.0668 -9.4174
## 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) 0.00 1 1 1
## (1 | HNDid) 37.48 1 kept <1e-07
##
## Fixed effects:
## Sum Sq Mean Sq NumDF DenDF F.value elim.num
## Age:IPVstatus:Sex:Race 1308.12 1308.12 1 109.21 0.9360 1
## Age:IPVstatus:Sex 125.74 125.74 1 110.96 0.0697 2
## IPVstatus:Sex:Race 769.23 769.23 1 52.78 0.5062 3
## Age:Sex:Race 1360.61 1360.61 1 112.33 1.1206 4
## Sex:Race 26.97 26.97 1 53.80 0.0187 5
## Age:Sex 1824.25 1824.25 1 114.64 1.1873 6
## Age:IPVstatus:Race 2597.76 2597.76 1 115.28 1.3823 7
## Age:IPVstatus 51.37 51.37 1 116.87 0.1378 8
## Age:Race 184.66 184.66 1 116.29 0.3649 9
## IPVstatus:Race 941.75 941.75 1 56.89 0.6440 10
## Age 13383.73 13383.73 1 119.16 9.3438 kept
## IPVstatus 666.83 666.83 1 57.71 1.2850 kept
## Sex 3485.23 3485.23 1 57.97 6.4636 kept
## Race 8282.63 8282.63 1 57.67 4.5432 kept
## IPVstatus:Sex 13491.72 13491.72 1 57.66 9.2609 kept
## Pr(>F)
## Age:IPVstatus:Sex:Race 0.3354
## Age:IPVstatus:Sex 0.7923
## IPVstatus:Sex:Race 0.4799
## Age:Sex:Race 0.2921
## Sex:Race 0.8918
## Age:Sex 0.2782
## Age:IPVstatus:Race 0.2421
## Age:IPVstatus 0.7111
## Age:Race 0.5470
## IPVstatus:Race 0.4256
## Age 0.0028
## IPVstatus 0.2617
## Sex 0.0137
## Race 0.0373
## IPVstatus:Sex 0.0035
##
## Least squares means:
## IPVstatus Sex Race Estimate Standard Error DF
## IPVstatus 0 1.0 NA NA 96.8 10.7 57.7
## IPVstatus 1 2.0 NA NA 117.3 15.0 57.7
## Sex Women NA 2.0 NA 84.0 12.3 57.7
## Sex Men NA 1.0 NA 130.1 13.7 57.9
## Race White NA NA 2.0 88.2 14.4 57.7
## Race AfrAm NA NA 1.0 125.9 11.1 57.7
## IPVstatus:Sex 0 Women 1.0 2.0 NA 101.3 14.7 57.8
## IPVstatus:Sex 1 Women 2.0 2.0 NA 66.6 19.5 57.7
## IPVstatus:Sex 0 Men 1.0 1.0 NA 92.2 15.2 57.8
## IPVstatus:Sex 1 Men 2.0 1.0 NA 168.0 22.6 57.8
## t-value Lower CI Upper CI p-value
## IPVstatus 0 9.07 75.4 118 <2e-16
## IPVstatus 1 7.83 87.3 147 <2e-16
## Sex Women 6.83 59.4 109 <2e-16
## Sex Men 9.48 102.7 158 <2e-16
## Race White 6.13 59.4 117 <2e-16
## Race AfrAm 11.31 103.6 148 <2e-16
## IPVstatus:Sex 0 Women 6.89 71.9 131 <2e-16
## IPVstatus:Sex 1 Women 3.42 27.7 106 0.0011
## IPVstatus:Sex 0 Men 6.09 61.9 123 <2e-16
## IPVstatus:Sex 1 Men 7.43 122.7 213 <2e-16
##
## Differences of LSMEANS:
## Estimate Standard Error DF t-value
## IPVstatus 0-1 -20.5 18.11 57.7 -1.13
## Sex Women-Men -46.1 18.15 58.0 -2.54
## Race White-AfrAm -37.6 17.66 57.7 -2.13
## IPVstatus:Sex 0 Women- 1 Women 34.7 24.19 57.7 1.43
## IPVstatus:Sex 0 Women- 0 Men 9.1 20.87 57.9 0.44
## IPVstatus:Sex 0 Women- 1 Men -66.7 26.67 58.0 -2.50
## IPVstatus:Sex 1 Women- 0 Men -25.6 24.56 57.7 -1.04
## IPVstatus:Sex 1 Women- 1 Men -101.4 29.70 57.7 -3.41
## IPVstatus:Sex 0 Men- 1 Men -75.8 27.01 57.7 -2.81
## Lower CI Upper CI p-value
## IPVstatus 0-1 -56.8 15.72 0.262
## Sex Women-Men -82.5 -9.81 0.014
## Race White-AfrAm -73.0 -2.29 0.037
## IPVstatus:Sex 0 Women- 1 Women -13.7 83.15 0.157
## IPVstatus:Sex 0 Women- 0 Men -32.7 50.89 0.664
## IPVstatus:Sex 0 Women- 1 Men -120.0 -13.27 0.015
## IPVstatus:Sex 1 Women- 0 Men -74.8 23.55 0.301
## IPVstatus:Sex 1 Women- 1 Men -160.8 -41.92 0.001
## IPVstatus:Sex 0 Men- 1 Men -129.8 -21.70 0.007
##
## Final model:
## lme4::lmer(formula = TrailsBlow ~ Age + IPVstatus + Sex + Race +
## (1 | HNDid) + IPVstatus:Sex, data = IPVandCognitionDataSet2,
## REML = reml, contrasts = l)
Re-run the suggested final Model 1
(mm1 = lmer(TrailsBlow ~ Age + IPVstatus + Sex + Race + (Age | HNDid) + (1 |
subclass) + IPVstatus:Sex, 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: TrailsBlow ~ Age + IPVstatus + Sex + Race + (Age | HNDid) + (1 | subclass) + IPVstatus:Sex
## Data: IPVandCognitionDataSet2
## AIC BIC logLik deviance
## 1392 1423 -685 1370
## Random effects:
## Groups Name Std.Dev. Corr
## HNDid (Intercept) 75.47
## Age 2.51 0.90
## subclass (Intercept) 0.00
## Residual 33.70
## Number of obs: 126, groups: HNDid, 63; subclass, 21
## Fixed Effects:
## (Intercept) Age IPVstatus1
## 97.51 2.27 -33.60
## SexMen RaceAfrAm IPVstatus1:SexMen
## -15.51 41.37 118.05
summary(mm1)
## Warning: number of observations <= rank(Z); variance-covariance matrix will be unidentifiable
## Warning: number of observations <= rank(Z); variance-covariance matrix will be unidentifiable
## Linear mixed model fit by maximum likelihood ['merModLmerTest']
## Formula: TrailsBlow ~ Age + IPVstatus + Sex + Race + (Age | HNDid) + (1 | subclass) + IPVstatus:Sex
## Data: IPVandCognitionDataSet2
##
## AIC BIC logLik deviance
## 1392 1423 -685 1370
##
## Random effects:
## Groups Name Variance Std.Dev. Corr
## HNDid (Intercept) 5696.0 75.47
## Age 6.3 2.51 0.90
## subclass (Intercept) 0.0 0.00
## Residual 1135.9 33.70
## Number of obs: 126, groups: HNDid, 63; subclass, 21
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 97.512 20.333 67.800 4.80 9.2e-06
## Age 2.272 0.976 48.300 2.33 0.02409
## IPVstatus1 -33.596 21.949 61.500 -1.53 0.13098
## SexMen -15.506 18.868 60.100 -0.82 0.41442
## RaceAfrAm 41.367 15.979 57.900 2.59 0.01216
## IPVstatus1:SexMen 118.054 33.374 62.500 3.54 0.00077
##
## Correlation of Fixed Effects:
## (Intr) Age IPVst1 SexMen RcAfrA
## Age 0.585
## IPVstatus1 -0.452 -0.101
## SexMen -0.501 -0.116 0.393
## RaceAfrAm -0.552 -0.040 0.085 0.053
## IPVstts1:SM 0.313 0.076 -0.660 -0.569 -0.075
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(TrailsBlow ~ (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: TrailsBlow ~ (Age + IPVstatus + Sex + Race + CES1)^5 + (Age | HNDid) + (1 | subclass)
## Data: IPVandCognitionDataSet2
## AIC BIC logLik deviance
## 1416.8 1521.7 -671.4 1342.8
## Random effects:
## Groups Name Std.Dev. Corr
## HNDid (Intercept) 7.71e+01
## Age 3.69e+00 1.00
## subclass (Intercept) 5.07e-04
## Residual 3.29e+01
## Number of obs: 126, groups: HNDid, 63; subclass, 21
## Fixed Effects:
## (Intercept)
## 100.306
## Age
## 2.747
## IPVstatus1
## 5.694
## SexMen
## -30.238
## RaceAfrAm
## 21.680
## CES11
## -36.320
## Age:IPVstatus1
## 1.586
## Age:SexMen
## -0.362
## Age:RaceAfrAm
## -1.414
## Age:CES11
## -2.316
## IPVstatus1:SexMen
## 147.826
## IPVstatus1:RaceAfrAm
## -51.769
## IPVstatus1:CES11
## -5.082
## SexMen:RaceAfrAm
## 8.801
## SexMen:CES11
## 122.121
## RaceAfrAm:CES11
## 100.474
## Age:IPVstatus1:SexMen
## 4.530
## Age:IPVstatus1:RaceAfrAm
## -2.029
## Age:IPVstatus1:CES11
## -2.162
## Age:SexMen:RaceAfrAm
## 0.209
## Age:SexMen:CES11
## 3.682
## Age:RaceAfrAm:CES11
## 5.626
## IPVstatus1:SexMen:RaceAfrAm
## 97.700
## IPVstatus1:SexMen:CES11
## -175.307
## IPVstatus1:RaceAfrAm:CES11
## -47.501
## SexMen:RaceAfrAm:CES11
## -87.560
## Age:IPVstatus1:SexMen:RaceAfrAm
## -5.267
## Age:IPVstatus1:SexMen:CES11
## -0.704
## Age:IPVstatus1:RaceAfrAm:CES11
## 1.769
## Age:SexMen:RaceAfrAm:CES11
## 2.393
## IPVstatus1:SexMen:RaceAfrAm:CES11
## 16.165
## Age:IPVstatus1:SexMen:RaceAfrAm:CES11
## -3.990
(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 term (1 | subclass) was eliminated because of standard deviation being equal to 0
##
## Random effects:
## Chi.sq Chi.DF elim.num p.value
## (1 | HNDid) 31.48 1 kept < 1e-07
##
## Fixed effects:
## Sum Sq Mean Sq NumDF DenDF F.value
## Age:IPVstatus:Sex:Race:CES1 200.20 200.20 1 64.41 0.1331
## Age:IPVstatus:Sex:CES1 59.78 59.78 1 66.70 0.0490
## Age:IPVstatus:Race:CES1 42.52 42.52 1 81.47 0.0599
## Age:IPVstatus:CES1 5.83 5.83 1 89.01 0.0046
## IPVstatus:Sex:Race:CES1 101.16 101.16 1 54.03 0.1028
## IPVstatus:Race:CES1 186.84 186.84 1 48.68 0.0608
## Age:Sex:Race:CES1 730.73 730.73 1 98.47 0.4930
## Age:IPVstatus:Sex:Race 396.98 396.98 1 100.98 0.3572
## Age:IPVstatus:Sex 165.40 165.40 1 101.90 0.0642
## Age:Sex:CES1 1213.50 1213.50 1 100.52 0.3773
## Age:Sex:Race 1326.22 1326.22 1 102.95 0.2991
## Sex:Race:CES1 1049.67 1049.67 1 47.11 0.7183
## Age:IPVstatus:Race 1467.03 1467.03 1 104.64 0.7277
## Age:IPVstatus 105.02 105.02 1 106.57 0.0010
## Age:Race:CES1 1322.63 1322.63 1 107.60 0.5925
## Race:CES1 44.92 44.92 1 49.59 0.0000
## Age:CES1 277.84 277.84 1 109.92 0.0167
## Age:Race 378.23 378.23 1 108.44 0.0385
## Age:Sex 1952.41 1952.41 1 108.75 1.7815
## IPVstatus:Sex:Race 1920.56 1920.56 1 50.76 2.6993
## IPVstatus:Race 1030.99 1030.99 1 51.80 0.0241
## Sex:Race 191.51 191.51 1 53.25 0.3072
## IPVstatus:Sex:CES1 4085.23 4085.23 1 53.77 3.8489
## Sex:CES1 454.72 454.72 1 54.69 0.3533
## IPVstatus:CES1 5233.81 5233.81 1 55.94 3.6517
## CES1 840.00 840.00 1 57.13 0.0891
## Age 13552.74 13552.74 1 119.16 9.3438
## IPVstatus 685.17 685.17 1 57.71 1.2850
## Sex 3581.71 3581.71 1 57.97 6.4636
## Race 8506.49 8506.49 1 57.67 4.5432
## IPVstatus:Sex 12868.56 12868.56 1 57.66 9.2609
## elim.num Pr(>F)
## Age:IPVstatus:Sex:Race:CES1 1 0.7164
## Age:IPVstatus:Sex:CES1 2 0.8254
## Age:IPVstatus:Race:CES1 3 0.8072
## Age:IPVstatus:CES1 4 0.9461
## IPVstatus:Sex:Race:CES1 5 0.7497
## IPVstatus:Race:CES1 6 0.8062
## Age:Sex:Race:CES1 7 0.4843
## Age:IPVstatus:Sex:Race 8 0.5514
## Age:IPVstatus:Sex 9 0.8004
## Age:Sex:CES1 10 0.5404
## Age:Sex:Race 11 0.5856
## Sex:Race:CES1 12 0.4010
## Age:IPVstatus:Race 13 0.3956
## Age:IPVstatus 14 0.9753
## Age:Race:CES1 15 0.4432
## Race:CES1 16 0.9986
## Age:CES1 17 0.8975
## Age:Race 18 0.8448
## Age:Sex 19 0.1848
## IPVstatus:Sex:Race 20 0.1066
## IPVstatus:Race 21 0.8772
## Sex:Race 22 0.5817
## IPVstatus:Sex:CES1 23 0.0550
## Sex:CES1 24 0.5547
## IPVstatus:CES1 25 0.0611
## CES1 26 0.7664
## Age kept 0.0028
## IPVstatus kept 0.2617
## Sex kept 0.0137
## Race kept 0.0373
## IPVstatus:Sex kept 0.0035
##
## Least squares means:
## IPVstatus Sex Race Estimate Standard Error DF
## IPVstatus 0 1.0 NA NA 96.8 10.7 57.7
## IPVstatus 1 2.0 NA NA 117.3 15.0 57.7
## Sex Women NA 2.0 NA 84.0 12.3 57.7
## Sex Men NA 1.0 NA 130.1 13.7 57.9
## Race White NA NA 2.0 88.2 14.4 57.7
## Race AfrAm NA NA 1.0 125.9 11.1 57.7
## IPVstatus:Sex 0 Women 1.0 2.0 NA 101.3 14.7 57.8
## IPVstatus:Sex 1 Women 2.0 2.0 NA 66.6 19.5 57.7
## IPVstatus:Sex 0 Men 1.0 1.0 NA 92.2 15.2 57.8
## IPVstatus:Sex 1 Men 2.0 1.0 NA 168.0 22.6 57.8
## t-value Lower CI Upper CI p-value
## IPVstatus 0 9.07 75.4 118 <2e-16
## IPVstatus 1 7.83 87.3 147 <2e-16
## Sex Women 6.83 59.4 109 <2e-16
## Sex Men 9.48 102.7 158 <2e-16
## Race White 6.13 59.4 117 <2e-16
## Race AfrAm 11.31 103.6 148 <2e-16
## IPVstatus:Sex 0 Women 6.89 71.9 131 <2e-16
## IPVstatus:Sex 1 Women 3.42 27.7 106 0.0011
## IPVstatus:Sex 0 Men 6.09 61.9 123 <2e-16
## IPVstatus:Sex 1 Men 7.43 122.7 213 <2e-16
##
## Differences of LSMEANS:
## Estimate Standard Error DF t-value
## IPVstatus 0-1 -20.5 18.11 57.7 -1.13
## Sex Women-Men -46.1 18.15 58.0 -2.54
## Race White-AfrAm -37.6 17.66 57.7 -2.13
## IPVstatus:Sex 0 Women- 1 Women 34.7 24.19 57.7 1.43
## IPVstatus:Sex 0 Women- 0 Men 9.1 20.87 57.9 0.44
## IPVstatus:Sex 0 Women- 1 Men -66.7 26.67 58.0 -2.50
## IPVstatus:Sex 1 Women- 0 Men -25.6 24.56 57.7 -1.04
## IPVstatus:Sex 1 Women- 1 Men -101.4 29.70 57.7 -3.41
## IPVstatus:Sex 0 Men- 1 Men -75.8 27.01 57.7 -2.81
## Lower CI Upper CI p-value
## IPVstatus 0-1 -56.8 15.72 0.262
## Sex Women-Men -82.5 -9.81 0.014
## Race White-AfrAm -73.0 -2.29 0.037
## IPVstatus:Sex 0 Women- 1 Women -13.7 83.15 0.157
## IPVstatus:Sex 0 Women- 0 Men -32.7 50.89 0.664
## IPVstatus:Sex 0 Women- 1 Men -120.0 -13.27 0.015
## IPVstatus:Sex 1 Women- 0 Men -74.8 23.55 0.301
## IPVstatus:Sex 1 Women- 1 Men -160.8 -41.92 0.001
## IPVstatus:Sex 0 Men- 1 Men -129.8 -21.70 0.007
##
## Final model:
## lme4::lmer(formula = TrailsBlow ~ Age + IPVstatus + Sex + Race +
## (1 | HNDid) + IPVstatus:Sex, data = IPVandCognitionDataSet2,
## REML = reml, contrasts = l)
Re-run the suggested final Model 2
(mm2 = lmer(TrailsBlow ~ Age + IPVstatus + Sex + Race + (Age | HNDid) + (1 |
subclass) + IPVstatus:Sex, 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: TrailsBlow ~ Age + IPVstatus + Sex + Race + (Age | HNDid) + (1 | subclass) + IPVstatus:Sex
## Data: IPVandCognitionDataSet2
## AIC BIC logLik deviance
## 1392 1423 -685 1370
## Random effects:
## Groups Name Std.Dev. Corr
## HNDid (Intercept) 75.47
## Age 2.51 0.90
## subclass (Intercept) 0.00
## Residual 33.70
## Number of obs: 126, groups: HNDid, 63; subclass, 21
## Fixed Effects:
## (Intercept) Age IPVstatus1
## 97.51 2.27 -33.60
## SexMen RaceAfrAm IPVstatus1:SexMen
## -15.51 41.37 118.05
summary(mm2)
## Warning: number of observations <= rank(Z); variance-covariance matrix will be unidentifiable
## Warning: number of observations <= rank(Z); variance-covariance matrix will be unidentifiable
## Linear mixed model fit by maximum likelihood ['merModLmerTest']
## Formula: TrailsBlow ~ Age + IPVstatus + Sex + Race + (Age | HNDid) + (1 | subclass) + IPVstatus:Sex
## Data: IPVandCognitionDataSet2
##
## AIC BIC logLik deviance
## 1392 1423 -685 1370
##
## Random effects:
## Groups Name Variance Std.Dev. Corr
## HNDid (Intercept) 5696.0 75.47
## Age 6.3 2.51 0.90
## subclass (Intercept) 0.0 0.00
## Residual 1135.9 33.70
## Number of obs: 126, groups: HNDid, 63; subclass, 21
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 97.512 20.333 67.800 4.80 9.2e-06
## Age 2.272 0.976 48.300 2.33 0.02409
## IPVstatus1 -33.596 21.949 61.500 -1.53 0.13098
## SexMen -15.506 18.868 60.100 -0.82 0.41442
## RaceAfrAm 41.367 15.979 57.900 2.59 0.01216
## IPVstatus1:SexMen 118.054 33.374 62.500 3.54 0.00077
##
## Correlation of Fixed Effects:
## (Intr) Age IPVst1 SexMen RcAfrA
## Age 0.585
## IPVstatus1 -0.452 -0.101
## SexMen -0.501 -0.116 0.393
## RaceAfrAm -0.552 -0.040 0.085 0.053
## IPVstts1:SM 0.313 0.076 -0.660 -0.569 -0.075
plot(st)
plot(mm2)