Lifetime IPV and Hypertension Plots

Age/BMI/IPV Interaction (BMI is continuous)

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

library(zUtil)
library(zStat)
load("~/Desktop/IPV and Hypertension/Data Analysis/LifeIPVbp.rda")

pAge = seq(30,70)
pBMI = seq(15,60)

(mm1 = lmer(adjSBP ~Age + LifeIPV + Sex + PovStat + BMI + Age:LifeIPV + Age:Sex + Age:PovStat + Age:BMI + LifeIPV:BMI + Sex:PovStat + Age:LifeIPV:BMI + Age:Sex:PovStat + (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 + Sex + PovStat + BMI + Age:LifeIPV +      Age:Sex + Age:PovStat + Age:BMI + LifeIPV:BMI + Sex:PovStat +      Age:LifeIPV:BMI + Age:Sex:PovStat + (Age | HNDid) + (1 |      subclass) 
##    Data: LifeIPVbp 
## REML criterion at convergence: 5492 
## Random effects:
##  Groups   Name        Std.Dev. Corr
##  HNDid    (Intercept) 1.18e+01     
##           Age         3.33e-01 1.00
##  subclass (Intercept) 2.61e-04     
##  Residual             1.14e+01     
## Number of obs: 666, groups: HNDid, 334; subclass, 222
## Fixed Effects:
##             (Intercept)                      Age                 LifeIPV1  
##                 90.2417                   0.4940                  10.8264  
##                  SexMen             PovStatBelow                      BMI  
##                 -0.5942                   0.3619                   1.0221  
##            Age:LifeIPV1               Age:SexMen         Age:PovStatBelow  
##                  2.2796                  -0.5595                  -0.3295  
##                 Age:BMI             LifeIPV1:BMI      SexMen:PovStatBelow  
##                  0.0136                  -0.3254                   8.7477  
##        Age:LifeIPV1:BMI  Age:SexMen:PovStatBelow  
##                 -0.0778                   1.1013

hatIPVhyp1 = zMixHat(LifeIPVbp, mm1, vary = "Age=pAge, BMI = pBMI,LifeIPV=zQ(0,1)",fixedCov=c("Sex","PovStat"))

fit.A<-hatIPVhyp1[hatIPVhyp1$LifeIPV==0,]
fit.B<-hatIPVhyp1[hatIPVhyp1$LifeIPV==1,]

par(mfrow=c(1,2),mai=c(0,0.03,0.5,0) + 0.01)
persp(x=seq(30,70,1), y=seq(15,60,1), z=matrix(fit.A$hat, nrow=41, ncol=46, byrow=F), xlab="Age",
      ylab="BMI",cex.lab = 1.5,col="light blue", zlab="fit", main="No IPV",cex.main = 1.5) 
persp(x=seq(30,70,1), y=seq(15,60,1), z=matrix(fit.B$hat, nrow=41, ncol=46, byrow=F), xlab="Age",
      ylab="BMI",cex.lab = 1.5,col="light green", zlab="fit", main="IPV",cex.main = 1.5)