I centered agenew to Age50 = (agenew-50)/10

Attention


     Simultaneous Tests for General Linear Hypotheses

Fit: lmer(formula = Attention ~ imtleftmm * Age50 * Race * PovStat + 
    Sex + HseHldEducation + PhysMeanSBPsit + LabResChol + PhysBMI + 
    rxHTN + rxHypercholesterolemia + MedHxDiabetes + CVDclustersum + 
    CES + alcoholever + smokingever + marijever + harddrugever + 
    (Age50 | HNDid), data = imtcog, control = lmerControl(check.nobs.vs.nRE = "ignore"))

Linear Hypotheses:
                                      Estimate   Std. Error  z value   Pr(>|z|)
(Intercept) == 0                   6.334719963  0.692909486  9.14220 < 2.22e-16
imtleftmm == 0                    -0.488571284  0.724574001 -0.67429 0.50012847
Age50 == 0                         0.275810802  0.474729691  0.58098 0.56125060
Race == 0                         -1.509984033  0.722539778 -2.08983 0.03663323
PovStat == 0                      -0.794156076  0.885058126 -0.89729 0.36956282
Sex == 0                          -0.372992264  0.102943029 -3.62329 0.00029088
HseHldEducation == 0               0.124888238  0.016562068  7.54062 4.6851e-14
PhysMeanSBPsit == 0               -0.003057879  0.003079997 -0.99282 0.32079829
LabResChol == 0                    0.002382399  0.001216312  1.95871 0.05014714
PhysBMI == 0                      -0.012697251  0.007367665 -1.72338 0.08482070
rxHTN == 0                        -0.191098142  0.130282088 -1.46680 0.14242969
rxHypercholesterolemia == 0        0.468093567  0.176360046  2.65419 0.00794984
MedHxDiabetes == 0                -0.449118410  0.182907540 -2.45544 0.01407124
CVDclustersum == 0                 0.059243983  0.102144196  0.58000 0.56191231
CES == 0                          -0.014820108  0.004633650 -3.19837 0.00138209
alcoholever == 0                   0.077640782  0.126127877  0.61557 0.53817707
smokingever == 0                   0.183894082  0.118660098  1.54976 0.12120033
marijever == 0                     0.175797492  0.116960473  1.50305 0.13282603
harddrugever == 0                  0.180701856  0.130855999  1.38092 0.16730311
imtleftmm:Age50 == 0              -0.814941056  0.731931962 -1.11341 0.26553198
imtleftmm:Race == 0                0.931646801  1.032739511  0.90211 0.36699733
Age50:Race == 0                   -0.989502479  0.707986894 -1.39763 0.16222473
imtleftmm:PovStat == 0             0.533777620  1.296458320  0.41172 0.68054478
Age50:PovStat == 0                -0.464304340  0.883346095 -0.52562 0.59915228
Race:PovStat == 0                  1.448179773  1.145673178  1.26404 0.20621472
imtleftmm:Age50:Race == 0          1.326843633  1.033429045  1.28392 0.19916879
imtleftmm:Age50:PovStat == 0       0.933961254  1.329902762  0.70228 0.48250590
imtleftmm:Race:PovStat == 0       -1.885569833  1.645634249 -1.14580 0.25187738
Age50:Race:PovStat == 0            0.999215788  1.135281660  0.88015 0.37877918
imtleftmm:Age50:Race:PovStat == 0 -1.729768332  1.670751520 -1.03532 0.30051785
(Univariate p values reported)

BVRtot


     Simultaneous Tests for General Linear Hypotheses

Fit: lmer(formula = BVRtot ~ imtleftmm * Age50 * Race * PovStat + 
    Sex + HseHldEducation + PhysMeanSBPsit + LabResChol + PhysBMI + 
    rxHTN + rxHypercholesterolemia + MedHxDiabetes + CVDclustersum + 
    CES + alcoholever + smokingever + marijever + harddrugever + 
    (Age50 | HNDid), data = imtcog, control = lmerControl(check.nobs.vs.nRE = "ignore"))

Linear Hypotheses:
                                       Estimate    Std. Error  z value   Pr(>|z|)
(Intercept) == 0                   8.3977292862  1.4802440436  5.67321 1.4015e-08
imtleftmm == 0                     0.7498302704  1.5371664023  0.48780  0.6256913
Age50 == 0                         1.4588651057  0.9714956363  1.50167  0.1331826
Race == 0                          4.7033450309  1.5873933686  2.96294  0.0030472
PovStat == 0                       1.4790252315  1.9219849879  0.76953  0.4415787
Sex == 0                          -0.9123579753  0.2182655604 -4.18004 2.9146e-05
HseHldEducation == 0              -0.3276373473  0.0352647028 -9.29080 < 2.22e-16
PhysMeanSBPsit == 0                0.0124410385  0.0067181884  1.85184  0.0640482
LabResChol == 0                   -0.0007292721  0.0025955658 -0.28097  0.7787346
PhysBMI == 0                       0.0044423928  0.0155021711  0.28657  0.7744448
rxHTN == 0                        -0.5064292934  0.2847914797 -1.77825  0.0753635
rxHypercholesterolemia == 0       -0.3598476397  0.3996202537 -0.90047  0.3678681
MedHxDiabetes == 0                 0.0746992779  0.3991961023  0.18712  0.8515632
CVDclustersum == 0                -0.1200127987  0.2246058304 -0.53433  0.5931158
CES == 0                           0.0697629262  0.0097723247  7.13883 9.4125e-13
alcoholever == 0                  -0.2260799037  0.2682971591 -0.84265  0.3994257
smokingever == 0                  -0.0219569717  0.2503708771 -0.08770  0.9301169
marijever == 0                    -0.1554958335  0.2470848157 -0.62932  0.5291385
harddrugever == 0                  0.0747763323  0.2751715756  0.27174  0.7858186
imtleftmm:Age50 == 0               0.2630355288  1.4886218947  0.17670  0.8597461
imtleftmm:Race == 0               -4.3868169061  2.2459704491 -1.95319  0.0507966
Age50:Race == 0                    1.3810766948  1.4869307724  0.92881  0.3529874
imtleftmm:PovStat == 0            -0.9662498957  2.7849647277 -0.34695  0.7286272
Age50:PovStat == 0                -0.0147675360  1.8689477041 -0.00790  0.9936956
Race:PovStat == 0                 -2.2625042374  2.5174264658 -0.89874  0.3687928
imtleftmm:Age50:Race == 0         -1.1773855121  2.1597353358 -0.54515  0.5856485
imtleftmm:Age50:PovStat == 0      -0.2011314561  2.8061241712 -0.07168  0.9428598
imtleftmm:Race:PovStat == 0        1.7067097927  3.5795531183  0.47679  0.6335088
Age50:Race:PovStat == 0            0.4054743894  2.4096483123  0.16827  0.8663699
imtleftmm:Age50:Race:PovStat == 0 -0.5234283102  3.5360745660 -0.14803  0.8823228
(Univariate p values reported)

CVLtca


     Simultaneous Tests for General Linear Hypotheses

Fit: lmer(formula = CVLtca ~ imtleftmm * Age50 * Race * PovStat + 
    Sex + HseHldEducation + PhysMeanSBPsit + LabResChol + PhysBMI + 
    rxHTN + rxHypercholesterolemia + MedHxDiabetes + CVDclustersum + 
    CES + alcoholever + smokingever + marijever + harddrugever + 
    (Age50 | HNDid), data = imtcog, control = lmerControl(check.nobs.vs.nRE = "ignore"))

Linear Hypotheses:
                                      Estimate   Std. Error  z value   Pr(>|z|)
(Intercept) == 0                  19.277224443  2.656939358  7.25543 4.0035e-13
imtleftmm == 0                    -2.320534387  2.776842252 -0.83567  0.4033384
Age50 == 0                        -5.241381111  1.836071297 -2.85467  0.0043081
Race == 0                         -7.532407624  2.795041361 -2.69492  0.0070406
PovStat == 0                      -4.021636222  3.411238798 -1.17894  0.2384232
Sex == 0                          -3.025591119  0.396582871 -7.62915 2.3537e-14
HseHldEducation == 0               0.640433739  0.063803543 10.03759 < 2.22e-16
PhysMeanSBPsit == 0               -0.003370745  0.011811404 -0.28538  0.7753526
LabResChol == 0                   -0.007498687  0.004705495 -1.59360  0.1110252
PhysBMI == 0                      -0.002800398  0.028645027 -0.09776  0.9221212
rxHTN == 0                        -0.017310951  0.498288702 -0.03474  0.9722864
rxHypercholesterolemia == 0        1.238592659  0.661901072  1.87127  0.0613083
MedHxDiabetes == 0                -0.014516114  0.685735991 -0.02117  0.9831111
CVDclustersum == 0                -0.654360869  0.372274545 -1.75774  0.0787922
CES == 0                          -0.093006089  0.017923794 -5.18897 2.1146e-07
alcoholever == 0                   0.174270845  0.489771100  0.35582  0.7219746
smokingever == 0                   0.367025448  0.459335598  0.79904  0.4242698
marijever == 0                    -0.029657497  0.453043881 -0.06546  0.9478056
harddrugever == 0                  0.717885697  0.506747873  1.41665  0.1565845
imtleftmm:Age50 == 0               3.692265333  2.832089337  1.30372  0.1923274
imtleftmm:Race == 0                6.810569807  4.001957181  1.70181  0.0887910
Age50:Race == 0                    3.575075952  2.787304267  1.28263  0.1996223
imtleftmm:PovStat == 0             4.753607986  5.003514334  0.95005  0.3420849
Age50:PovStat == 0                 2.899499755  3.475076027  0.83437  0.4040724
Race:PovStat == 0                  5.742652149  4.452794427  1.28967  0.1971640
imtleftmm:Age50:Race == 0         -4.012637060  4.063016094 -0.98760  0.3233483
imtleftmm:Age50:PovStat == 0      -2.757815526  5.201330774 -0.53021  0.5959639
imtleftmm:Race:PovStat == 0       -6.786768546  6.406099509 -1.05942  0.2894072
Age50:Race:PovStat == 0           -4.924470964  4.504402434 -1.09326  0.2742808
imtleftmm:Age50:Race:PovStat == 0  4.753953793  6.598498098  0.72046  0.4712418
(Univariate p values reported)