load(file="/Users/dleibel1/Box Sync/R Data/DanThesisFinal.rdata")
library(lmerTest)
## Loading required package: Matrix
## Loading required package: lme4
##
## Attaching package: 'lmerTest'
## The following object is masked from 'package:lme4':
##
## lmer
## The following object is masked from 'package:stats':
##
## step
library(zStat)
library(zUtil)
##Model 5: Final model (Significant Interactions Retained)
mm5 = lmer(PhyPerfSingleMN~Age + Sex + EF + Race + BMI + PovStat + WRATtotal + (1|HNDid) + Age*Race + Age*EF ,data=DanThesisFinal,REML=F)
summary(mm5)
## Linear mixed model fit by maximum likelihood t-tests use Satterthwaite
## approximations to degrees of freedom [lmerMod]
## Formula:
## PhyPerfSingleMN ~ Age + Sex + EF + Race + BMI + PovStat + WRATtotal +
## (1 | HNDid) + Age * Race + Age * EF
## Data: DanThesisFinal
##
## AIC BIC logLik deviance df.resid
## 8520.5 8584.9 -4248.2 8496.5 1579
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -5.1365 -0.0659 0.1569 0.3788 2.6634
##
## Random effects:
## Groups Name Variance Std.Dev.
## HNDid (Intercept) 4.814 2.194
## Residual 7.990 2.827
## Number of obs: 1591, groups: HNDid, 1112
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 3.053e+01 8.405e-01 7.741e+02 36.327 < 2e-16 ***
## Age -1.552e-01 1.843e-02 9.181e+02 -8.417 < 2e-16 ***
## SexMen 1.370e-01 2.005e-01 6.855e+02 0.683 0.494642
## EF 1.560e-01 4.542e-02 1.321e+03 3.435 0.000611 ***
## RaceAfrAm 7.627e-01 2.152e-01 7.245e+02 3.544 0.000419 ***
## BMI -1.215e-01 1.464e-02 8.185e+02 -8.301 4.44e-16 ***
## PovStatBelow -3.531e-01 2.172e-01 7.169e+02 -1.626 0.104465
## WRATtotal 2.120e-02 1.526e-02 7.717e+02 1.389 0.165241
## Age:RaceAfrAm 6.831e-02 2.316e-02 8.904e+02 2.950 0.003260 **
## Age:EF 1.220e-02 4.557e-03 1.276e+03 2.677 0.007515 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) Age SexMen EF RcAfrA BMI PvSttB WRATtt Ag:RAA
## Age 0.052
## SexMen -0.194 -0.060
## EF 0.223 -0.001 -0.002
## RaceAfrAm -0.312 -0.108 -0.020 0.136
## BMI -0.502 0.024 0.142 0.036 -0.030
## PovStatBelw -0.275 0.049 0.049 0.076 -0.043 0.100
## WRATtotal -0.819 -0.048 0.017 -0.361 0.228 -0.028 0.172
## Age:RcAfrAm -0.064 -0.797 0.038 0.028 0.128 0.003 0.035 0.045
## Age:EF -0.020 -0.309 0.050 0.228 0.058 -0.026 -0.041 0.031 0.264
##OLD zHAT: Plot Age*Race interaction in Final Model
pAge = seq(-19,20)
hatPhyPerfSingleMN = zMixHat(DanThesisFinal, mm5, vary = "Age=pAge, Race=zQ(AfrAm,White)",fixedCov=c("BMI","Sex","EF","PovStat","WRATtotal"))
with(hatPhyPerfSingleMN[hatPhyPerfSingleMN$Race == 'AfrAm',],plot(pAge,hat, lty=1, col = "red", type = "l",ylim = c(24,32), ylab = "Time(Sec)", xlab = "Age"))
with(hatPhyPerfSingleMN[hatPhyPerfSingleMN$Race == "White",], lines(pAge,hat, lty=2, col = "black"))
axis(1,at=c(-20,-15,-10,-5,0,5,10,15,20),labels = c("30","35","40","45","50","55","60","65","70"))
legend(-20,32, zQ(AfrAm,White), lty=(1:2), col = "black",cex=.75,bty="n")
##NEW zHAT: Plot Age*Race interaction in Final Model
plotData = zHat(DanThesisFinal, mm5, xAxis='Age', factors=('Race'))
par(las=1, lwd=2)
plotData$AgeUn = plotData$Age + 50
with(plotData[plotData$Race=='AfrAm',], plot (AgeUn, Hat, lty =1, typ='l', ylim=c(22,32), ylab='Single Leg Stand', xlab='Age'))
with(plotData[plotData$Race=='White',], lines(AgeUn, Hat, lty =2))
legend(55, 32, c('African American','White'), lty=1:2)
