Clock Drawing Regression Models with CDT Dichotomous Variable Split at the Median

Clock Total Regression Model 1

load("~/Desktop/Megan/Research/IPV and Cognition Paper/IPV R Output/IPVandCognitionDataSet2.rda")

library(lme4)
## Loading required package: Matrix
library(lmerTest)
## 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

(mm1 = lmer(BinaryClocks ~ (Age + IPVstatus + Sex + PovStat)^4 + (Age | HNDid) + 
    (1 | subclass), data = IPVandCognitionDataSet2))
## Warning: number of observations <= rank(Z); variance-covariance matrix
## will be unidentifiable
## Linear mixed model fit by REML ['merModLmerTest']
## Formula: BinaryClocks ~ (Age + IPVstatus + Sex + PovStat)^4 + (Age | HNDid) +      (1 | subclass) 
##    Data: IPVandCognitionDataSet2 
## REML criterion at convergence: 198.1 
## Random effects:
##  Groups   Name        Std.Dev. Corr
##  HNDid    (Intercept) 0.2690       
##           Age         0.0168   1.00
##  subclass (Intercept) 0.2049       
##  Residual             0.3780       
## Number of obs: 126, groups: HNDid, 63; subclass, 21
## Fixed Effects:
##                        (Intercept)                                 Age  
##                            1.56668                            -0.00605  
##                         IPVstatus1                              SexMen  
##                            0.07766                             0.30672  
##                       PovStatBelow                      Age:IPVstatus1  
##                            0.16039                            -0.00468  
##                         Age:SexMen                    Age:PovStatBelow  
##                            0.01006                             0.02360  
##                  IPVstatus1:SexMen             IPVstatus1:PovStatBelow  
##                           -0.74214                            -0.86023  
##                SexMen:PovStatBelow               Age:IPVstatus1:SexMen  
##                           -0.31597                            -0.03714  
##        Age:IPVstatus1:PovStatBelow             Age:SexMen:PovStatBelow  
##                           -0.08988                            -0.03950  
##     IPVstatus1:SexMen:PovStatBelow  Age:IPVstatus1:SexMen:PovStatBelow  
##                            1.49279                             0.14653

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 REML ['merModLmerTest']
## Formula: BinaryClocks ~ (Age + IPVstatus + Sex + PovStat)^4 + (Age | HNDid) +      (1 | subclass) 
##    Data: IPVandCognitionDataSet2 
## 
## REML criterion at convergence: 198.1 
## 
## Random effects:
##  Groups   Name        Variance Std.Dev. Corr
##  HNDid    (Intercept) 0.072359 0.2690       
##           Age         0.000281 0.0168   1.00
##  subclass (Intercept) 0.041986 0.2049       
##  Residual             0.142899 0.3780       
## Number of obs: 126, groups: HNDid, 63; subclass, 21
## 
## Fixed effects:
##                                    Estimate Std. Error       df t value
## (Intercept)                         1.56668    0.17225 23.20000    9.10
## Age                                -0.00605    0.01366 33.20000   -0.44
## IPVstatus1                          0.07766    0.26480 22.20000    0.29
## SexMen                              0.30672    0.25779 21.60000    1.19
## PovStatBelow                        0.16039    0.28774 11.80000    0.56
## Age:IPVstatus1                     -0.00468    0.02446 41.50000   -0.19
## Age:SexMen                          0.01006    0.02171 30.40000    0.46
## Age:PovStatBelow                    0.02360    0.02332 12.30000    1.01
## IPVstatus1:SexMen                  -0.74214    0.43975 26.80000   -1.69
## IPVstatus1:PovStatBelow            -0.86023    0.60814 36.60000   -1.41
## SexMen:PovStatBelow                -0.31597    0.38390 12.70000   -0.82
## Age:IPVstatus1:SexMen              -0.03714    0.04006 49.50000   -0.93
## Age:IPVstatus1:PovStatBelow        -0.08988    0.05952 68.00000   -1.51
## Age:SexMen:PovStatBelow            -0.03950    0.04110 16.20000   -0.96
## IPVstatus1:SexMen:PovStatBelow      1.49279    0.75614 28.30000    1.97
## Age:IPVstatus1:SexMen:PovStatBelow  0.14653    0.07655 47.40000    1.91
##                                    Pr(>|t|)
## (Intercept)                         4.1e-09
## Age                                   0.661
## IPVstatus1                            0.772
## SexMen                                0.247
## PovStatBelow                          0.588
## Age:IPVstatus1                        0.849
## Age:SexMen                            0.646
## Age:PovStatBelow                      0.331
## IPVstatus1:SexMen                     0.103
## IPVstatus1:PovStatBelow               0.166
## SexMen:PovStatBelow                   0.426
## Age:IPVstatus1:SexMen                 0.358
## Age:IPVstatus1:PovStatBelow           0.136
## Age:SexMen:PovStatBelow               0.351
## IPVstatus1:SexMen:PovStatBelow        0.058
## Age:IPVstatus1:SexMen:PovStatBelow    0.062
## 
## Correlation of Fixed Effects:
##             (Intr) Age    IPVst1 SexMen PvSttB Ag:IPV1 Ag:SxM Ag:PSB
## Age          0.830                                                  
## IPVstatus1  -0.593 -0.508                                           
## SexMen      -0.625 -0.524  0.387                                    
## PovStatBelw -0.589 -0.505  0.400  0.382                             
## Ag:IPVstts1 -0.444 -0.504  0.853  0.280  0.304                      
## Age:SexMen  -0.498 -0.573  0.305  0.881  0.293  0.302               
## Ag:PvSttBlw -0.482 -0.574  0.329  0.303  0.825  0.332   0.326       
## IPVstts1:SM  0.352  0.309 -0.602 -0.530 -0.232 -0.514  -0.474 -0.201
## IPVstt1:PSB  0.328  0.264 -0.499 -0.218 -0.523 -0.413  -0.154 -0.420
## SxMn:PvSttB  0.439  0.369 -0.267 -0.670 -0.735 -0.192  -0.582 -0.593
## Ag:IPVs1:SM  0.272  0.320 -0.520 -0.449 -0.177 -0.620  -0.519 -0.208
## Ag:IPV1:PSB  0.218  0.241 -0.386 -0.133 -0.356 -0.444  -0.129 -0.418
## Ag:SxMn:PSB  0.264  0.300 -0.143 -0.484 -0.427 -0.145  -0.536 -0.518
## IPV1:SM:PSB -0.258 -0.209  0.382  0.351  0.417  0.313   0.291  0.328
## A:IPV1:SM:P -0.166 -0.189  0.277  0.263  0.253  0.329   0.282  0.332
##             IPVs1:SM IPV1:P SM:PSB Ag:IPV1:SM A:IPV1:P A:SM:P IPV1:SM:
## Age                                                                   
## IPVstatus1                                                            
## SexMen                                                                
## PovStatBelw                                                           
## Ag:IPVstts1                                                           
## Age:SexMen                                                            
## Ag:PvSttBlw                                                           
## IPVstts1:SM                                                           
## IPVstt1:PSB  0.297                                                    
## SxMn:PvSttB  0.366    0.372                                           
## Ag:IPVs1:SM  0.867    0.246  0.304                                    
## Ag:IPV1:PSB  0.230    0.880  0.241  0.268                             
## Ag:SxMn:PSB  0.232    0.203  0.657  0.262      0.199                  
## IPV1:SM:PSB -0.609   -0.795 -0.527 -0.515     -0.696   -0.318         
## A:IPV1:SM:P -0.454   -0.663 -0.356 -0.521     -0.770   -0.540  0.778

plot(st)
## Error: object 'st' not found

plot(mm1)

plot of chunk unnamed-chunk-1

Clock Total Regression Model 2 (with CES)

load("~/Desktop/Megan/Research/IPV and Cognition Paper/IPV R Output/IPVandCognitionDataSet2.rda")

library(lme4)
library(lmerTest)

(mm2 = lmer(BinaryClocks ~ (Age + IPVstatus + Sex + PovStat + CES1)^5 + (Age | 
    HNDid) + (1 | subclass), data = IPVandCognitionDataSet2))
## Warning: number of observations <= rank(Z); variance-covariance matrix
## will be unidentifiable
## Linear mixed model fit by REML ['merModLmerTest']
## Formula: BinaryClocks ~ (Age + IPVstatus + Sex + PovStat + CES1)^5 + (Age |      HNDid) + (1 | subclass) 
##    Data: IPVandCognitionDataSet2 
## REML criterion at convergence: 216.2 
## Random effects:
##  Groups   Name        Std.Dev. Corr
##  HNDid    (Intercept) 0.2033       
##           Age         0.0107   1.00
##  subclass (Intercept) 0.2367       
##  Residual             0.3807       
## Number of obs: 126, groups: HNDid, 63; subclass, 21
## Fixed Effects:
##                              (Intercept)  
##                                   1.5057  
##                                      Age  
##                                  -0.0197  
##                               IPVstatus1  
##                                  -0.4141  
##                                   SexMen  
##                                   0.4726  
##                             PovStatBelow  
##                                   0.0541  
##                                    CES11  
##                                   0.3206  
##                           Age:IPVstatus1  
##                                  -0.0453  
##                               Age:SexMen  
##                                   0.0330  
##                         Age:PovStatBelow  
##                                   0.0214  
##                                Age:CES11  
##                                   0.0463  
##                        IPVstatus1:SexMen  
##                                   0.3677  
##                  IPVstatus1:PovStatBelow  
##                                  -1.7406  
##                         IPVstatus1:CES11  
##                                   0.4663  
##                      SexMen:PovStatBelow  
##                                  -0.2768  
##                             SexMen:CES11  
##                                  -0.9412  
##                       PovStatBelow:CES11  
##                                  -0.1703  
##                    Age:IPVstatus1:SexMen  
##                                   0.0321  
##              Age:IPVstatus1:PovStatBelow  
##                                  -0.1564  
##                     Age:IPVstatus1:CES11  
##                                   0.0332  
##                  Age:SexMen:PovStatBelow  
##                                  -0.0710  
##                         Age:SexMen:CES11  
##                                  -0.1057  
##                   Age:PovStatBelow:CES11  
##                                  -0.0245  
##           IPVstatus1:SexMen:PovStatBelow  
##                                   1.8408  
##                  IPVstatus1:SexMen:CES11  
##                                  -0.5670  
##            IPVstatus1:PovStatBelow:CES11  
##                                   1.2381  
##                SexMen:PovStatBelow:CES11  
##                                   1.0246  
##       Age:IPVstatus1:SexMen:PovStatBelow  
##                                   0.2126  
##              Age:IPVstatus1:SexMen:CES11  
##                                  -0.0103  
##        Age:IPVstatus1:PovStatBelow:CES11  
##                                   0.0922  
##            Age:SexMen:PovStatBelow:CES11  
##                                   0.2526  
##     IPVstatus1:SexMen:PovStatBelow:CES11  
##                                  -1.6126  
## Age:IPVstatus1:SexMen:PovStatBelow:CES11  
##                                  -0.2385

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 REML ['merModLmerTest']
## Formula: BinaryClocks ~ (Age + IPVstatus + Sex + PovStat + CES1)^5 + (Age |      HNDid) + (1 | subclass) 
##    Data: IPVandCognitionDataSet2 
## 
## REML criterion at convergence: 216.2 
## 
## Random effects:
##  Groups   Name        Variance Std.Dev. Corr
##  HNDid    (Intercept) 0.041314 0.2033       
##           Age         0.000114 0.0107   1.00
##  subclass (Intercept) 0.056013 0.2367       
##  Residual             0.144941 0.3807       
## Number of obs: 126, groups: HNDid, 63; subclass, 21
## 
## Fixed effects:
##                                          Estimate Std. Error      df
## (Intercept)                                1.5057     0.2001  9.1000
## Age                                       -0.0197     0.0159 14.3000
## IPVstatus1                                -0.4141     0.4305 38.3000
## SexMen                                     0.4726     0.2713  6.9000
## PovStatBelow                               0.0541     0.4685 35.2000
## CES11                                      0.3206     0.3145 19.5000
## Age:IPVstatus1                            -0.0453     0.0407 76.1000
## Age:SexMen                                 0.0330     0.0226 10.4000
## Age:PovStatBelow                           0.0214     0.0421 63.9000
## Age:CES11                                  0.0463     0.0281 49.4000
## IPVstatus1:SexMen                          0.3677     2.3677 63.3000
## IPVstatus1:PovStatBelow                   -1.7406     1.3368 79.6000
## IPVstatus1:CES11                           0.4663     0.5628 30.6000
## SexMen:PovStatBelow                       -0.2768     0.5415 22.9000
## SexMen:CES11                              -0.9412     0.6139 42.3000
## PovStatBelow:CES11                        -0.1703     0.5946 19.9000
## Age:IPVstatus1:SexMen                      0.0321     0.1420 62.1000
## Age:IPVstatus1:PovStatBelow               -0.1564     0.1215 67.8000
## Age:IPVstatus1:CES11                       0.0332     0.0524 61.6000
## Age:SexMen:PovStatBelow                   -0.0710     0.0541 27.1000
## Age:SexMen:CES11                          -0.1057     0.0606 80.0000
## Age:PovStatBelow:CES11                    -0.0245     0.0508 36.3000
## IPVstatus1:SexMen:PovStatBelow             1.8408     2.7132 69.4000
## IPVstatus1:SexMen:CES11                   -0.5670     2.4617 69.4000
## IPVstatus1:PovStatBelow:CES11              1.2381     1.5074 75.1000
## SexMen:PovStatBelow:CES11                  1.0246     0.8951 30.0000
## Age:IPVstatus1:SexMen:PovStatBelow         0.2126     0.1869 65.9000
## Age:IPVstatus1:SexMen:CES11               -0.0103     0.1596 71.8000
## Age:IPVstatus1:PovStatBelow:CES11          0.0922     0.1420 80.1000
## Age:SexMen:PovStatBelow:CES11              0.2526     0.1140 72.8000
## IPVstatus1:SexMen:PovStatBelow:CES11      -1.6126     2.8873 76.6000
## Age:IPVstatus1:SexMen:PovStatBelow:CES11  -0.2385     0.2363 74.6000
##                                          t value Pr(>|t|)
## (Intercept)                                 7.52  3.5e-05
## Age                                        -1.24    0.235
## IPVstatus1                                 -0.96    0.342
## SexMen                                      1.74    0.126
## PovStatBelow                                0.12    0.909
## CES11                                       1.02    0.320
## Age:IPVstatus1                             -1.11    0.268
## Age:SexMen                                  1.46    0.174
## Age:PovStatBelow                            0.51    0.612
## Age:CES11                                   1.65    0.105
## IPVstatus1:SexMen                           0.16    0.877
## IPVstatus1:PovStatBelow                    -1.30    0.197
## IPVstatus1:CES11                            0.83    0.414
## SexMen:PovStatBelow                        -0.51    0.614
## SexMen:CES11                               -1.53    0.133
## PovStatBelow:CES11                         -0.29    0.778
## Age:IPVstatus1:SexMen                       0.23    0.822
## Age:IPVstatus1:PovStatBelow                -1.29    0.203
## Age:IPVstatus1:CES11                        0.63    0.528
## Age:SexMen:PovStatBelow                    -1.31    0.200
## Age:SexMen:CES11                           -1.74    0.085
## Age:PovStatBelow:CES11                     -0.48    0.633
## IPVstatus1:SexMen:PovStatBelow              0.68    0.500
## IPVstatus1:SexMen:CES11                    -0.23    0.819
## IPVstatus1:PovStatBelow:CES11               0.82    0.414
## SexMen:PovStatBelow:CES11                   1.14    0.261
## Age:IPVstatus1:SexMen:PovStatBelow          1.14    0.259
## Age:IPVstatus1:SexMen:CES11                -0.06    0.949
## Age:IPVstatus1:PovStatBelow:CES11           0.65    0.518
## Age:SexMen:PovStatBelow:CES11               2.22    0.030
## IPVstatus1:SexMen:PovStatBelow:CES11       -0.56    0.578
## Age:IPVstatus1:SexMen:PovStatBelow:CES11   -1.01    0.316
## 
## Correlation matrix not shown by default, as p = 32 > 20.
## Use print(x, correlation=TRUE)  or
##     vcov(x)   if you need it

Eliminate Non-significant Terms for Model 2

(mm2 = lmer(BinaryClocks ~ (Age + Sex + PovStat + CES1)^4 + (Age | HNDid) + 
    (1 | subclass), data = IPVandCognitionDataSet2))
## Warning: number of observations <= rank(Z); variance-covariance matrix
## will be unidentifiable
## Linear mixed model fit by REML ['merModLmerTest']
## Formula: BinaryClocks ~ (Age + Sex + PovStat + CES1)^4 + (Age | HNDid) +      (1 | subclass) 
##    Data: IPVandCognitionDataSet2 
## REML criterion at convergence: 192.1 
## Random effects:
##  Groups   Name        Std.Dev. Corr
##  HNDid    (Intercept) 0.1547       
##           Age         0.0106   1.00
##  subclass (Intercept) 0.2640       
##  Residual             0.3698       
## Number of obs: 126, groups: HNDid, 63; subclass, 21
## Fixed Effects:
##                   (Intercept)                            Age  
##                       1.47536                       -0.02184  
##                        SexMen                   PovStatBelow  
##                       0.50890                       -0.12635  
##                         CES11                     Age:SexMen  
##                       0.39283                        0.03458  
##              Age:PovStatBelow                      Age:CES11  
##                      -0.00112                        0.04767  
##           SexMen:PovStatBelow                   SexMen:CES11  
##                      -0.10413                       -1.15570  
##            PovStatBelow:CES11        Age:SexMen:PovStatBelow  
##                       0.01669                       -0.02378  
##              Age:SexMen:CES11         Age:PovStatBelow:CES11  
##                      -0.10459                       -0.00531  
##     SexMen:PovStatBelow:CES11  Age:SexMen:PovStatBelow:CES11  
##                       0.66552                        0.14711

(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 REML ['merModLmerTest']
## Formula: BinaryClocks ~ (Age + Sex + PovStat + CES1)^4 + (Age | HNDid) +      (1 | subclass) 
##    Data: IPVandCognitionDataSet2 
## 
## REML criterion at convergence: 192.1 
## 
## Random effects:
##  Groups   Name        Variance Std.Dev. Corr
##  HNDid    (Intercept) 0.023939 0.1547       
##           Age         0.000112 0.0106   1.00
##  subclass (Intercept) 0.069717 0.2640       
##  Residual             0.136754 0.3698       
## Number of obs: 126, groups: HNDid, 63; subclass, 21
## 
## Fixed effects:
##                               Estimate Std. Error       df t value
## (Intercept)                    1.47536    0.16539 23.70000    8.92
## Age                           -0.02184    0.01416 32.10000   -1.54
## SexMen                         0.50890    0.22896 14.40000    2.22
## PovStatBelow                  -0.12635    0.41124 65.30000   -0.31
## CES11                          0.39283    0.21427 23.00000    1.83
## Age:SexMen                     0.03458    0.01931 19.00000    1.79
## Age:PovStatBelow              -0.00112    0.03788 88.60000   -0.03
## Age:CES11                      0.04767    0.02143 49.80000    2.22
## SexMen:PovStatBelow           -0.10413    0.46803 44.90000   -0.22
## SexMen:CES11                  -1.15570    0.37369 27.80000   -3.09
## PovStatBelow:CES11             0.01669    0.47110 36.20000    0.04
## Age:SexMen:PovStatBelow       -0.02378    0.04275 63.20000   -0.56
## Age:SexMen:CES11              -0.10459    0.03777 56.00000   -2.77
## Age:PovStatBelow:CES11        -0.00531    0.04288 49.70000   -0.12
## SexMen:PovStatBelow:CES11      0.66552    0.63039 36.90000    1.06
## Age:SexMen:PovStatBelow:CES11  0.14711    0.07401 74.70000    1.99
##                               Pr(>|t|)
## (Intercept)                    4.8e-09
## Age                             0.1326
## SexMen                          0.0427
## PovStatBelow                    0.7596
## CES11                           0.0797
## Age:SexMen                      0.0892
## Age:PovStatBelow                0.9766
## Age:CES11                       0.0307
## SexMen:PovStatBelow             0.8249
## SexMen:CES11                    0.0045
## PovStatBelow:CES11              0.9719
## Age:SexMen:PovStatBelow         0.5801
## Age:SexMen:CES11                0.0076
## Age:PovStatBelow:CES11          0.9019
## SexMen:PovStatBelow:CES11       0.2980
## Age:SexMen:PovStatBelow:CES11   0.0505
## 
## Correlation of Fixed Effects:
##             (Intr) Age    SexMen PvSttB CES11  Ag:SxM Ag:PSB A:CES1
## Age          0.760                                                 
## SexMen      -0.556 -0.434                                          
## PovStatBelw -0.369 -0.310  0.232                                   
## CES11       -0.635 -0.559  0.378  0.249                            
## Age:SexMen  -0.462 -0.580  0.843  0.166  0.338                     
## Ag:PvSttBlw -0.296 -0.378  0.181  0.915  0.222  0.215              
## Age:CES11   -0.443 -0.638  0.249  0.185  0.778  0.378  0.252       
## SxMn:PvSttB  0.274  0.216 -0.483 -0.865 -0.157 -0.384 -0.791 -0.103
## SexMn:CES11  0.295  0.269 -0.535 -0.116 -0.533 -0.472 -0.124 -0.414
## PvStB:CES11  0.299  0.266 -0.192 -0.868 -0.417 -0.143 -0.803 -0.354
## Ag:SxMn:PSB  0.227  0.269 -0.395 -0.781 -0.133 -0.448 -0.836 -0.145
## Ag:SM:CES11  0.221  0.337 -0.371 -0.084 -0.423 -0.479 -0.134 -0.547
## A:PSB:CES11  0.241  0.328 -0.146 -0.799 -0.364 -0.188 -0.872 -0.456
## SM:PSB:CES1 -0.147 -0.130  0.324  0.650  0.251  0.256  0.613  0.213
## A:SM:PSB:CE -0.136 -0.185  0.202  0.503  0.179  0.239  0.531  0.229
##             SxM:PSB SM:CES PSB:CE Ag:SM:PSB A:SM:C A:PSB: SM:PSB:
## Age                                                              
## SexMen                                                           
## PovStatBelw                                                      
## CES11                                                            
## Age:SexMen                                                       
## Ag:PvSttBlw                                                      
## Age:CES11                                                        
## SxMn:PvSttB                                                      
## SexMn:CES11  0.263                                               
## PvStB:CES11  0.753   0.220                                       
## Ag:SxMn:PSB  0.850   0.202  0.681                                
## Ag:SM:CES11  0.176   0.838  0.184  0.199                         
## A:PSB:CES11  0.690   0.202  0.878  0.742     0.249               
## SM:PSB:CES1 -0.764  -0.586 -0.756 -0.636    -0.490 -0.669        
## A:SM:PSB:CE -0.539  -0.403 -0.539 -0.616    -0.478 -0.606  0.687