SBP Final ModelSystolic Blood Pressure
load("~/Desktop/IPV and Hypertension/Data Analysis/LifeIPVbp.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(adjSBP ~(Age + LifeIPV + PovStat + BMI)^4 + (Age|HNDid) + (1|subclass) ,LifeIPVbp))
## Warning: number of observations <= rank(Z); variance-covariance matrix
## will be unidentifiable
## Linear mixed model fit by REML ['merModLmerTest']
## Formula: adjSBP ~ (Age + LifeIPV + PovStat + BMI)^4 + (Age | HNDid) + (1 | subclass)
## Data: LifeIPVbp
## REML criterion at convergence: 5542
## Random effects:
## Groups Name Std.Dev. Corr
## HNDid (Intercept) 1.25e+01
## Age 3.63e-01 1.00
## subclass (Intercept) 3.07e-04
## Residual 1.16e+01
## Number of obs: 666, groups: HNDid, 336; subclass, 222
## Fixed Effects:
## (Intercept) Age
## 91.3163 1.4923
## LifeIPV1 PovStatBelow
## 18.9622 17.3968
## BMI Age:LifeIPV1
## 0.9953 0.2507
## Age:PovStatBelow Age:BMI
## -1.1547 -0.0168
## LifeIPV1:PovStatBelow LifeIPV1:BMI
## -32.6688 -0.6258
## PovStatBelow:BMI Age:LifeIPV1:PovStatBelow
## -0.4840 2.9046
## Age:LifeIPV1:BMI Age:PovStatBelow:BMI
## -0.0133 0.0322
## LifeIPV1:PovStatBelow:BMI Age:LifeIPV1:PovStatBelow:BMI
## 1.0869 -0.0985
(st = step(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
## 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 (1 | subclass) was eliminated because of standard deviation being equal to 0
## 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 | HNDid) 104.2 1 kept < 1e-07
##
## Fixed effects:
## Sum Sq Mean Sq NumDF DenDF F.value elim.num
## Age:LifeIPV:PovStat:BMI 4.787e+02 4.787e+02 1 563.0 3.5115 1
## Age:PovStat:BMI 3.686e+01 3.686e+01 1 543.8 0.1769 2
## Age:LifeIPV:PovStat 3.607e+01 3.607e+01 1 491.9 0.4214 3
## Age:PovStat 1.352e+02 1.352e+02 1 489.9 1.0218 4
## Age 1.118e+04 1.118e+04 1 575.8 18.6819 kept
## LifeIPV 9.095e-01 9.095e-01 1 439.3 0.1033 kept
## PovStat 3.085e+02 3.085e+02 1 449.1 0.2666 kept
## BMI 8.887e+03 8.887e+03 1 449.1 40.3467 kept
## Age:LifeIPV 3.541e+02 3.541e+02 1 575.8 2.6318 kept
## Age:BMI 5.382e+02 5.382e+02 1 567.0 6.1916 kept
## LifeIPV:PovStat 3.610e+00 3.610e+00 1 449.1 4.8770 kept
## LifeIPV:BMI 3.690e+01 3.690e+01 1 449.1 0.1026 kept
## PovStat:BMI 8.705e+01 8.705e+01 1 458.1 0.0035 kept
## Age:LifeIPV:BMI 4.638e+02 4.638e+02 1 567.0 4.1328 kept
## LifeIPV:PovStat:BMI 7.637e+02 7.637e+02 1 458.1 5.2749 kept
## Pr(>F)
## Age:LifeIPV:PovStat:BMI 0.0615
## Age:PovStat:BMI 0.6743
## Age:LifeIPV:PovStat 0.5165
## Age:PovStat 0.3126
## Age 0
## LifeIPV 0.7481
## PovStat 0.6059
## BMI <1e-07
## Age:LifeIPV 0.1053
## Age:BMI 0.0131
## LifeIPV:PovStat 0.0277
## LifeIPV:BMI 0.7489
## PovStat:BMI 0.9528
## Age:LifeIPV:BMI 0.0425
## LifeIPV:PovStat:BMI 0.0221
##
## Least squares means:
## LifeIPV PovStat Estimate Standard Error DF
## LifeIPV 0 1 NA 122.48 1.06 325
## LifeIPV 1 2 NA 122.91 1.42 324
## PovStat Above NA 1 121.08 1.16 328
## PovStat Below NA 2 124.31 1.34 324
## LifeIPV:PovStat 0 Above 1 1 120.97 1.23 330
## LifeIPV:PovStat 1 Above 2 1 121.19 1.95 327
## LifeIPV:PovStat 0 Below 1 2 124.00 1.73 326
## LifeIPV:PovStat 1 Below 2 2 124.62 2.06 323
## t-value Lower CI Upper CI p-value
## LifeIPV 0 116.0 120 125 <2e-16
## LifeIPV 1 86.6 120 126 <2e-16
## PovStat Above 104.8 119 123 <2e-16
## PovStat Below 92.5 122 127 <2e-16
## LifeIPV:PovStat 0 Above 98.0 119 123 <2e-16
## LifeIPV:PovStat 1 Above 62.0 117 125 <2e-16
## LifeIPV:PovStat 0 Below 71.8 121 127 <2e-16
## LifeIPV:PovStat 1 Below 60.4 121 129 <2e-16
##
## Differences of LSMEANS:
## Estimate Standard Error DF t-value
## LifeIPV 0-1 -0.4 1.768 324.4 -0.24
## PovStat Above-Below -3.2 1.778 326.5 -1.82
## LifeIPV:PovStat 0 Above- 1 Above -0.2 2.311 327.6 -0.10
## LifeIPV:PovStat 0 Above- 0 Below -3.0 2.133 329.1 -1.42
## LifeIPV:PovStat 0 Above- 1 Below -3.7 2.403 324.4 -1.52
## LifeIPV:PovStat 1 Above- 0 Below -2.8 2.608 326.3 -1.08
## LifeIPV:PovStat 1 Above- 1 Below -3.4 2.844 325.1 -1.21
## LifeIPV:PovStat 0 Below- 1 Below -0.6 2.689 323.9 -0.23
## Lower CI Upper CI p-value
## LifeIPV 0-1 -3.90 3.056 0.81
## PovStat Above-Below -6.73 0.265 0.07
## LifeIPV:PovStat 0 Above- 1 Above -4.77 4.319 0.92
## LifeIPV:PovStat 0 Above- 0 Below -7.23 1.159 0.16
## LifeIPV:PovStat 0 Above- 1 Below -8.38 1.072 0.13
## LifeIPV:PovStat 1 Above- 0 Below -7.94 2.320 0.28
## LifeIPV:PovStat 1 Above- 1 Below -9.02 2.168 0.23
## LifeIPV:PovStat 0 Below- 1 Below -5.91 4.673 0.82
##
## Final model:
## lme4::lmer(formula = adjSBP ~ Age + LifeIPV + PovStat + BMI +
## (1 | HNDid) + Age:LifeIPV + Age:BMI + LifeIPV:PovStat + LifeIPV:BMI +
## PovStat:BMI + Age:LifeIPV:BMI + LifeIPV:PovStat:BMI, data = LifeIPVbp,
## REML = reml, contrasts = l)
plot(st)
SBP Final Model
(mm1 = lmer(adjSBP ~Age + LifeIPV + PovStat + BMI + Age:LifeIPV + Age:BMI + LifeIPV:PovStat + LifeIPV:BMI + PovStat:BMI + Age:LifeIPV:BMI + LifeIPV:PovStat:BMI + (Age|HNDid) + (1|subclass),data = LifeIPVbp))
## Warning: number of observations <= rank(Z); variance-covariance matrix
## will be unidentifiable
## Linear mixed model fit by REML ['merModLmerTest']
## Formula: adjSBP ~ Age + LifeIPV + PovStat + BMI + Age:LifeIPV + Age:BMI + LifeIPV:PovStat + LifeIPV:BMI + PovStat:BMI + Age:LifeIPV:BMI + LifeIPV:PovStat:BMI + (Age | HNDid) + (1 | subclass)
## Data: LifeIPVbp
## REML criterion at convergence: 5536
## Random effects:
## Groups Name Std.Dev. Corr
## HNDid (Intercept) 1.27e+01
## Age 3.59e-01 1.00
## subclass (Intercept) 1.16e-04
## Residual 1.15e+01
## Number of obs: 666, groups: HNDid, 336; subclass, 222
## Fixed Effects:
## (Intercept) Age
## 89.51998 1.00113
## LifeIPV1 PovStatBelow
## 22.31151 22.29997
## BMI Age:LifeIPV1
## 1.04910 1.62225
## Age:BMI LifeIPV1:PovStatBelow
## -0.00332 -40.76430
## LifeIPV1:BMI PovStatBelow:BMI
## -0.73978 -0.61802
## Age:LifeIPV1:BMI LifeIPV1:PovStatBelow:BMI
## -0.06017 1.35789
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: adjSBP ~ Age + LifeIPV + PovStat + BMI + Age:LifeIPV + Age:BMI + LifeIPV:PovStat + LifeIPV:BMI + PovStat:BMI + Age:LifeIPV:BMI + LifeIPV:PovStat:BMI + (Age | HNDid) + (1 | subclass)
## Data: LifeIPVbp
##
## REML criterion at convergence: 5536
##
## Random effects:
## Groups Name Variance Std.Dev. Corr
## HNDid (Intercept) 1.61e+02 1.27e+01
## Age 1.29e-01 3.59e-01 1.00
## subclass (Intercept) 1.35e-08 1.16e-04
## Residual 1.33e+02 1.15e+01
## Number of obs: 666, groups: HNDid, 336; subclass, 222
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 89.51998 4.87723 400.00000 18.35 < 2e-16
## Age 1.00113 0.43057 513.00000 2.33 0.0205
## LifeIPV1 22.31151 9.82110 465.00000 2.27 0.0236
## PovStatBelow 22.29997 7.71302 362.00000 2.89 0.0041
## BMI 1.04910 0.15048 406.00000 6.97 1.3e-11
## Age:LifeIPV1 1.62225 0.81260 577.00000 2.00 0.0464
## Age:BMI -0.00332 0.01340 518.00000 -0.25 0.8045
## LifeIPV1:PovStatBelow -40.76430 13.66547 426.00000 -2.98 0.0030
## LifeIPV1:BMI -0.73978 0.30691 472.00000 -2.41 0.0163
## PovStatBelow:BMI -0.61802 0.24339 364.00000 -2.54 0.0115
## Age:LifeIPV1:BMI -0.06017 0.02526 570.00000 -2.38 0.0176
## LifeIPV1:PovStatBelow:BMI 1.35789 0.43126 433.00000 3.15 0.0018
##
## Correlation of Fixed Effects:
## (Intr) Age LfIPV1 PvSttB BMI Ag:LIPV1 Ag:BMI LfIPV1:PSB
## Age 0.353
## LifeIPV1 -0.497 -0.176
## PovStatBelw -0.554 0.016 0.275
## BMI -0.967 -0.371 0.480 0.534
## Age:LifIPV1 -0.187 -0.530 0.319 -0.009 0.196
## Age:BMI -0.366 -0.967 0.182 0.017 0.403 0.512
## LfIPV1:PvSB 0.313 -0.009 -0.667 -0.564 -0.301 -0.065 -0.009
## LifIPV1:BMI 0.474 0.182 -0.971 -0.262 -0.490 -0.291 -0.198 0.651
## PvSttBl:BMI 0.522 0.018 -0.259 -0.965 -0.537 -0.010 -0.042 0.545
## A:LIPV1:BMI 0.194 0.513 -0.291 -0.009 -0.214 -0.972 -0.530 0.056
## LIPV1:PSB:B -0.295 -0.010 0.646 0.545 0.303 0.052 0.024 -0.969
## LIPV1:B PSB:BM A:LIPV1:
## Age
## LifeIPV1
## PovStatBelw
## BMI
## Age:LifIPV1
## Age:BMI
## LfIPV1:PvSB
## LifIPV1:BMI
## PvSttBl:BMI 0.264
## A:LIPV1:BMI 0.280 0.022
## LIPV1:PSB:B -0.667 -0.564 -0.041
plot(mm1)
Diastolic Blood Pressure
(mm1 = lmer(adjDBP ~(Age + LifeIPV + PovStat + BMI)^4 + (Age|HNDid) + (1|subclass) ,LifeIPVbp))
## Warning: number of observations <= rank(Z); variance-covariance matrix
## will be unidentifiable
## Linear mixed model fit by REML ['merModLmerTest']
## Formula: adjDBP ~ (Age + LifeIPV + PovStat + BMI)^4 + (Age | HNDid) + (1 | subclass)
## Data: LifeIPVbp
## REML criterion at convergence: 4915
## Random effects:
## Groups Name Std.Dev. Corr
## HNDid (Intercept) 6.13e+00
## Age 4.22e-02 1.00
## subclass (Intercept) 1.73e-05
## Residual 7.79e+00
## Number of obs: 666, groups: HNDid, 336; subclass, 222
## Fixed Effects:
## (Intercept) Age
## 61.14020 0.67127
## LifeIPV1 PovStatBelow
## 7.44039 4.04631
## BMI Age:LifeIPV1
## 0.32231 0.29003
## Age:PovStatBelow Age:BMI
## -0.99950 -0.01903
## LifeIPV1:PovStatBelow LifeIPV1:BMI
## -15.80756 -0.23966
## PovStatBelow:BMI Age:LifeIPV1:PovStatBelow
## -0.07986 0.62698
## Age:LifeIPV1:BMI Age:PovStatBelow:BMI
## -0.00844 0.03477
## LifeIPV1:PovStatBelow:BMI Age:LifeIPV1:PovStatBelow:BMI
## 0.59050 -0.02989
(st = step(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
## 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
## Warning: number of observations <= rank(Z); variance-covariance matrix will be unidentifiable
##
## Random effects:
## Chi.sq Chi.DF elim.num p.value
## (1 | subclass) 0.00 1 1 1
## (Age + 0 | HNDid) 0.00 1 2 1
## (1 | HNDid) 50.51 1 kept <1e-07
##
## Fixed effects:
## Sum Sq Mean Sq NumDF DenDF F.value elim.num
## Age:LifeIPV:PovStat:BMI 60.811 60.811 1 504.1 1.0043 1
## Age:LifeIPV:PovStat 79.877 79.877 1 442.6 1.9480 2
## Age:LifeIPV:BMI 79.764 79.764 1 508.6 2.2841 3
## Age:LifeIPV 67.638 67.638 1 439.9 0.9147 4
## Age:PovStat:BMI 257.266 257.266 1 482.1 2.5958 5
## Age:PovStat 2.957 2.957 1 442.1 0.2161 6
## Age:BMI 230.886 230.886 1 485.9 3.3575 7
## Age 54.712 54.712 1 448.1 1.1078 8
## LifeIPV 90.868 90.868 1 418.1 0.0216 kept
## PovStat 335.409 335.409 1 418.1 0.4040 kept
## BMI 2220.725 2220.725 1 424.4 26.9439 kept
## LifeIPV:PovStat 133.883 133.883 1 418.1 3.1165 kept
## LifeIPV:BMI 19.759 19.759 1 424.4 0.2124 kept
## PovStat:BMI 26.659 26.659 1 424.4 1.9488 kept
## LifeIPV:PovStat:BMI 338.152 338.152 1 424.4 5.1037 kept
## Pr(>F)
## Age:LifeIPV:PovStat:BMI 0.3168
## Age:LifeIPV:PovStat 0.1635
## Age:LifeIPV:BMI 0.1313
## Age:LifeIPV 0.3394
## Age:PovStat:BMI 0.1078
## Age:PovStat 0.6422
## Age:BMI 0.0675
## Age 0.2931
## LifeIPV 0.8833
## PovStat 0.5254
## BMI 0
## LifeIPV:PovStat 0.0782
## LifeIPV:BMI 0.6451
## PovStat:BMI 0.1634
## LifeIPV:PovStat:BMI 0.0244
##
## Least squares means:
## LifeIPV PovStat Estimate Standard Error DF
## LifeIPV 0 1 NA 71.800 0.593 330
## LifeIPV 1 2 NA 73.020 0.794 327
## PovStat Above NA 1 70.946 0.644 329
## PovStat Below NA 2 73.874 0.753 328
## LifeIPV:PovStat 0 Above 1 1 71.223 0.690 333
## LifeIPV:PovStat 1 Above 2 1 70.669 1.087 328
## LifeIPV:PovStat 0 Below 1 2 72.377 0.964 328
## LifeIPV:PovStat 1 Below 2 2 75.371 1.157 327
## t-value Lower CI Upper CI p-value
## LifeIPV 0 121.2 70.6 73.0 <2e-16
## LifeIPV 1 92.0 71.5 74.6 <2e-16
## PovStat Above 110.2 69.7 72.2 <2e-16
## PovStat Below 98.1 72.4 75.4 <2e-16
## LifeIPV:PovStat 0 Above 103.3 69.9 72.6 <2e-16
## LifeIPV:PovStat 1 Above 65.0 68.5 72.8 <2e-16
## LifeIPV:PovStat 0 Below 75.1 70.5 74.3 <2e-16
## LifeIPV:PovStat 1 Below 65.1 73.1 77.6 <2e-16
##
## Differences of LSMEANS:
## Estimate Standard Error DF t-value
## LifeIPV 0-1 -1.2 0.991 328.3 -1.23
## PovStat Above-Below -2.9 0.991 328.3 -2.96
## LifeIPV:PovStat 0 Above- 1 Above 0.6 1.287 329.1 0.43
## LifeIPV:PovStat 0 Above- 0 Below -1.2 1.185 329.9 -0.97
## LifeIPV:PovStat 0 Above- 1 Below -4.1 1.347 328.9 -3.08
## LifeIPV:PovStat 1 Above- 0 Below -1.7 1.453 327.8 -1.18
## LifeIPV:PovStat 1 Above- 1 Below -4.7 1.587 327.4 -2.96
## LifeIPV:PovStat 0 Below- 1 Below -3.0 1.506 327.7 -1.99
## Lower CI Upper CI p-value
## LifeIPV 0-1 -3.17 0.7287 0.219
## PovStat Above-Below -4.88 -0.9794 0.003
## LifeIPV:PovStat 0 Above- 1 Above -1.98 3.0859 0.667
## LifeIPV:PovStat 0 Above- 0 Below -3.49 1.1774 0.331
## LifeIPV:PovStat 0 Above- 1 Below -6.80 -1.4980 0.002
## LifeIPV:PovStat 1 Above- 0 Below -4.57 1.1497 0.240
## LifeIPV:PovStat 1 Above- 1 Below -7.83 -1.5789 0.003
## LifeIPV:PovStat 0 Below- 1 Below -5.96 -0.0312 0.048
##
## Final model:
## lme4::lmer(formula = adjDBP ~ LifeIPV + PovStat + BMI + (1 |
## HNDid) + LifeIPV:PovStat + LifeIPV:BMI + PovStat:BMI + LifeIPV:PovStat:BMI,
## data = LifeIPVbp, REML = reml, contrasts = l)
plot(st)
Diastolic Blood Pressure Final Model
(mm1 = lmer(adjDBP ~LifeIPV + PovStat + BMI + LifeIPV:PovStat + LifeIPV:BMI + PovStat:BMI + LifeIPV:PovStat:BMI + (Age|HNDid) + (1|subclass) ,data = LifeIPVbp))
## Warning: number of observations <= rank(Z); variance-covariance matrix
## will be unidentifiable
## Linear mixed model fit by REML ['merModLmerTest']
## Formula: adjDBP ~ LifeIPV + PovStat + BMI + LifeIPV:PovStat + LifeIPV:BMI + PovStat:BMI + LifeIPV:PovStat:BMI + (Age | HNDid) + (1 | subclass)
## Data: LifeIPVbp
## REML criterion at convergence: 4891
## Random effects:
## Groups Name Std.Dev. Corr
## HNDid (Intercept) 6.3155
## Age 0.0147 1.00
## subclass (Intercept) 0.0000
## Residual 7.7352
## Number of obs: 666, groups: HNDid, 336; subclass, 222
## Fixed Effects:
## (Intercept) LifeIPV1
## 60.112 6.472
## PovStatBelow BMI
## 4.720 0.358
## LifeIPV1:PovStatBelow LifeIPV1:BMI
## -14.380 -0.227
## PovStatBelow:BMI LifeIPV1:PovStatBelow:BMI
## -0.116 0.581
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: adjDBP ~ LifeIPV + PovStat + BMI + LifeIPV:PovStat + LifeIPV:BMI + PovStat:BMI + LifeIPV:PovStat:BMI + (Age | HNDid) + (1 | subclass)
## Data: LifeIPVbp
##
## REML criterion at convergence: 4891
##
## Random effects:
## Groups Name Variance Std.Dev. Corr
## HNDid (Intercept) 3.99e+01 6.3155
## Age 2.17e-04 0.0147 1.00
## subclass (Intercept) 0.00e+00 0.0000
## Residual 5.98e+01 7.7352
## Number of obs: 666, groups: HNDid, 336; subclass, 222
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 60.1119 2.7032 386.0000 22.24 < 2e-16
## LifeIPV1 6.4719 5.5246 429.0000 1.17 0.242
## PovStatBelow 4.7203 4.5629 390.0000 1.03 0.302
## BMI 0.3583 0.0827 383.0000 4.33 1.9e-05
## LifeIPV1:PovStatBelow -14.3803 8.0469 418.0000 -1.79 0.075
## LifeIPV1:BMI -0.2275 0.1736 438.0000 -1.31 0.191
## PovStatBelow:BMI -0.1159 0.1444 395.0000 -0.80 0.422
## LifeIPV1:PovStatBelow:BMI 0.5812 0.2538 424.0000 2.29 0.023
##
## Correlation of Fixed Effects:
## (Intr) LfIPV1 PvSttB BMI LfIPV1:PSB LIPV1:B PSB:BM
## LifeIPV1 -0.489
## PovStatBelw -0.592 0.290
## BMI -0.967 0.473 0.573
## LfIPV1:PvSB 0.336 -0.687 -0.567 -0.325
## LifIPV1:BMI 0.461 -0.973 -0.273 -0.476 0.668
## PvSttBl:BMI 0.554 -0.271 -0.966 -0.573 0.548 0.273
## LIPV1:PSB:B -0.315 0.665 0.549 0.326 -0.969 -0.684 -0.569