Dan's Thesis Analyses - Single Leg Stand (Mean)
load(file="/Users/meganwilliams/Desktop/UMBC 2016/Dan's Thesis/DanThesisFinal.rdata")
library(lmerTest)
library(zUtil)
library(zStat)
Single Leg Stand (Mean) - Model 1 (Main Effects)
mm1 = lmer(PhyPerfSingleMN~Age + Sex + EF + Race + BMI + PovStat + WRATtotal + (1|HNDid), data=DanThesisFinal,REML=F)
summary(mm1)
## 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)
## Data: DanThesisFinal
##
## AIC BIC logLik deviance df.resid
## 8529.0 8582.7 -4254.5 8509.0 1581
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -5.2488350 -0.0758669 0.1729614 0.3802845 2.6114149
##
## Random effects:
## Groups Name Variance Std.Dev.
## HNDid (Intercept) 4.777249 2.185692
## Residual 8.109560 2.847729
## Number of obs: 1591, groups: HNDid, 1112
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 30.69807418 0.84078349 763.09050000 36.51127 < 2.22e-16
## Age -0.10798063 0.01100725 867.77850000 -9.80995 < 2.22e-16
## SexMen 0.09801145 0.20059620 674.04710000 0.48860 0.6252833
## EF 0.13181846 0.04433891 1250.57480000 2.97297 0.0030058
## RaceAfrAm 0.67004740 0.21382079 689.59580000 3.13369 0.0017994
## BMI -0.12082193 0.01466923 805.28890000 -8.23642 6.6613e-16
## PovStatBelow -0.35301061 0.21728448 703.11080000 -1.62465 0.1046859
## WRATtotal 0.01854419 0.01528047 761.25850000 1.21359 0.2252816
##
## Correlation of Fixed Effects:
## (Intr) Age SexMen EF RcAfrA BMI PvSttB
## Age 0.001
## SexMen -0.193 -0.043
## EF 0.232 0.078 -0.013
## RaceAfrAm -0.307 -0.006 -0.026 0.131
## BMI -0.503 0.041 0.144 0.043 -0.030
## PovStatBelw -0.274 0.121 0.050 0.090 -0.047 0.098
## WRATtotal -0.819 -0.018 0.014 -0.378 0.224 -0.027 0.172
Single Leg Stand (Mean) - Model 2 (Two-Way Interactions)
mm2 = lmer(PhyPerfSingleMN~(Age + Sex + EF + Race)^2 + BMI + PovStat + WRATtotal + (1|HNDid), data=DanThesisFinal,REML=F)
summary(mm2)
## Linear mixed model fit by maximum likelihood t-tests use Satterthwaite
## approximations to degrees of freedom [lmerMod]
## Formula: PhyPerfSingleMN ~ (Age + Sex + EF + Race)^2 + BMI + PovStat +
## WRATtotal + (1 | HNDid)
## Data: DanThesisFinal
##
## AIC BIC logLik deviance df.resid
## 8525.0 8611.0 -4246.5 8493.0 1575
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -5.0977145 -0.0709687 0.1563843 0.3809606 2.6387646
##
## Random effects:
## Groups Name Variance Std.Dev.
## HNDid (Intercept) 4.784148 2.187269
## Residual 7.987273 2.826176
## Number of obs: 1591, groups: HNDid, 1112
##
## Fixed effects:
## Estimate Std. Error df t value
## (Intercept) 3.030088e+01 8.528121e-01 7.895034e+02 35.53055
## Age -1.514995e-01 2.081789e-02 9.273897e+02 -7.27737
## SexMen 4.813023e-01 3.245822e-01 7.303491e+02 1.48284
## EF 2.006874e-01 7.476538e-02 1.134858e+03 2.68423
## RaceAfrAm 1.011599e+00 2.934380e-01 7.683536e+02 3.44740
## BMI -1.210151e-01 1.484117e-02 8.223581e+02 -8.15401
## PovStatBelow -3.518779e-01 2.171123e-01 7.203831e+02 -1.62072
## WRATtotal 2.281010e-02 1.530127e-02 7.806898e+02 1.49073
## Age:SexMen -1.492972e-02 2.201654e-02 8.747103e+02 -0.67811
## Age:EF 1.262432e-02 4.569193e-03 1.272253e+03 2.76292
## Age:RaceAfrAm 7.096341e-02 2.320795e-02 8.938358e+02 3.05772
## SexMen:EF -1.206776e-01 8.164043e-02 1.163073e+03 -1.47816
## SexMen:RaceAfrAm -5.336895e-01 4.191874e-01 7.273958e+02 -1.27315
## EF:RaceAfrAm 2.213173e-02 8.166355e-02 1.141608e+03 0.27101
## Pr(>|t|)
## (Intercept) < 2.22e-16
## Age 7.2498e-13
## SexMen 0.1385492
## EF 0.0073756
## RaceAfrAm 0.0005968
## BMI 1.3323e-15
## PovStatBelow 0.1055156
## WRATtotal 0.1364358
## Age:SexMen 0.4978789
## Age:EF 0.0058112
## Age:RaceAfrAm 0.0022967
## SexMen:EF 0.1396359
## SexMen:RaceAfrAm 0.2033706
## EF:RaceAfrAm 0.7864315
Single Leg Stand (Mean) - Model 3 (Three-Way Interactions)
mm3 = lmer(PhyPerfSingleMN~(Age + Sex + EF + Race)^3 + BMI + PovStat + WRATtotal + (1|HNDid), data=DanThesisFinal,REML=F)
summary(mm3)
## Linear mixed model fit by maximum likelihood t-tests use Satterthwaite
## approximations to degrees of freedom [lmerMod]
## Formula: PhyPerfSingleMN ~ (Age + Sex + EF + Race)^3 + BMI + PovStat +
## WRATtotal + (1 | HNDid)
## Data: DanThesisFinal
##
## AIC BIC logLik deviance df.resid
## 8531.6 8639.1 -4245.8 8491.6 1571
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -5.0464990 -0.0745487 0.1555329 0.3835197 2.6538498
##
## Random effects:
## Groups Name Variance Std.Dev.
## HNDid (Intercept) 4.832037 2.198190
## Residual 7.940914 2.817963
## Number of obs: 1591, groups: HNDid, 1112
##
## Fixed effects:
## Estimate Std. Error df t value
## (Intercept) 3.035110e+01 8.549985e-01 7.967688e+02 35.49842
## Age -1.512194e-01 2.617183e-02 1.063002e+03 -5.77795
## SexMen 4.024961e-01 3.420634e-01 8.012986e+02 1.17667
## EF 1.573029e-01 8.819673e-02 1.197822e+03 1.78355
## RaceAfrAm 9.808975e-01 2.989628e-01 8.134697e+02 3.28100
## BMI -1.208190e-01 1.486960e-02 8.292488e+02 -8.12524
## PovStatBelow -3.594479e-01 2.174570e-01 7.274022e+02 -1.65296
## WRATtotal 2.252123e-02 1.532329e-02 7.904950e+02 1.46974
## Age:SexMen -9.999182e-03 3.736094e-02 9.235866e+02 -0.26764
## Age:EF 8.579493e-03 8.351058e-03 1.350861e+03 1.02735
## Age:RaceAfrAm 7.333641e-02 3.216398e-02 9.999285e+02 2.28008
## SexMen:EF -2.807411e-02 1.255520e-01 1.162409e+03 -0.22361
## SexMen:RaceAfrAm -4.613367e-01 4.323552e-01 7.830047e+02 -1.06703
## EF:RaceAfrAm 8.491041e-02 1.160871e-01 1.189143e+03 0.73144
## Age:SexMen:EF 7.203205e-03 9.169950e-03 1.282918e+03 0.78552
## Age:SexMen:RaceAfrAm -1.246083e-02 4.687610e-02 9.038141e+02 -0.26582
## Age:EF:RaceAfrAm 1.469279e-03 9.322333e-03 1.311008e+03 0.15761
## SexMen:EF:RaceAfrAm -1.330890e-01 1.638047e-01 1.156455e+03 -0.81249
## Pr(>|t|)
## (Intercept) < 2.22e-16
## Age 9.9259e-09
## SexMen 0.2396762
## EF 0.0747507
## RaceAfrAm 0.0010784
## BMI 1.7764e-15
## PovStatBelow 0.0987703
## WRATtotal 0.1420306
## Age:SexMen 0.7890383
## Age:EF 0.3044377
## Age:RaceAfrAm 0.0228128
## SexMen:EF 0.8231036
## SexMen:RaceAfrAm 0.2862864
## EF:RaceAfrAm 0.4646563
## Age:SexMen:EF 0.4322922
## Age:SexMen:RaceAfrAm 0.7904349
## Age:EF:RaceAfrAm 0.8747896
## SexMen:EF:RaceAfrAm 0.4166801
Single Leg Stand (Mean) - Model 4 (Four-Way Interactions)
mm4 = lmer(PhyPerfSingleMN~(Age + Sex + EF + Race)^4 + BMI + PovStat + WRATtotal + (1|HNDid), data=DanThesisFinal,REML=F)
summary(mm4)
## Linear mixed model fit by maximum likelihood t-tests use Satterthwaite
## approximations to degrees of freedom [lmerMod]
## Formula: PhyPerfSingleMN ~ (Age + Sex + EF + Race)^4 + BMI + PovStat +
## WRATtotal + (1 | HNDid)
## Data: DanThesisFinal
##
## AIC BIC logLik deviance df.resid
## 8533.3 8646.1 -4245.6 8491.3 1570
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -5.0363359 -0.0701187 0.1551624 0.3854203 2.6545342
##
## Random effects:
## Groups Name Variance Std.Dev.
## HNDid (Intercept) 4.825661 2.196739
## Residual 7.943160 2.818361
## Number of obs: 1591, groups: HNDid, 1112
##
## Fixed effects:
## Estimate Std. Error df t value
## (Intercept) 3.033670e+01 8.551624e-01 7.984572e+02 35.47478
## Age -1.555139e-01 2.715584e-02 1.118261e+03 -5.72672
## SexMen 4.119001e-01 3.423626e-01 8.094397e+02 1.20311
## EF 1.677361e-01 8.991776e-02 1.241896e+03 1.86544
## RaceAfrAm 9.910859e-01 2.993992e-01 8.204185e+02 3.31025
## BMI -1.205657e-01 1.487241e-02 8.317833e+02 -8.10667
## PovStatBelow -3.630823e-01 2.174946e-01 7.266198e+02 -1.66939
## WRATtotal 2.244452e-02 1.532046e-02 7.908078e+02 1.46500
## Age:SexMen -2.200092e-03 3.959552e-02 1.001395e+03 -0.05556
## Age:EF 1.162318e-02 9.798822e-03 1.370856e+03 1.18618
## Age:RaceAfrAm 7.727310e-02 3.283748e-02 1.039909e+03 2.35320
## SexMen:EF -4.823993e-02 1.300422e-01 1.240921e+03 -0.37096
## SexMen:RaceAfrAm -4.638914e-01 4.322832e-01 7.844191e+02 -1.07312
## EF:RaceAfrAm 6.874809e-02 1.192287e-01 1.239648e+03 0.57661
## Age:SexMen:EF 5.805039e-04 1.443775e-02 1.374945e+03 0.04021
## Age:SexMen:RaceAfrAm -1.991600e-02 4.851988e-02 9.646169e+02 -0.41047
## Age:EF:RaceAfrAm -3.685673e-03 1.274302e-02 1.318590e+03 -0.28923
## SexMen:EF:RaceAfrAm -1.043131e-01 1.708075e-01 1.257488e+03 -0.61071
## Age:SexMen:EF:RaceAfrAm 1.109226e-02 1.869537e-02 1.313699e+03 0.59332
## Pr(>|t|)
## (Intercept) < 2.22e-16
## Age 1.3149e-08
## SexMen 0.22928524
## EF 0.06235552
## RaceAfrAm 0.00097282
## BMI 1.7764e-15
## PovStatBelow 0.09547182
## WRATtotal 0.14331761
## Age:SexMen 0.95570010
## Age:EF 0.23575631
## Age:RaceAfrAm 0.01879814
## SexMen:EF 0.71073361
## SexMen:RaceAfrAm 0.28354767
## EF:RaceAfrAm 0.56430980
## Age:SexMen:EF 0.96793364
## Age:SexMen:RaceAfrAm 0.68155162
## Age:EF:RaceAfrAm 0.77245036
## SexMen:EF:RaceAfrAm 0.54150486
## Age:SexMen:EF:RaceAfrAm 0.55307170
Single Leg Stand (Mean) - Model 5 (Retaining significant higher-order terms)
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
## -5.1364581 -0.0658631 0.1568661 0.3788438 2.6633921
##
## Random effects:
## Groups Name Variance Std.Dev.
## HNDid (Intercept) 4.814149 2.194117
## Residual 7.989653 2.826597
## Number of obs: 1591, groups: HNDid, 1112
##
## Fixed effects:
## Estimate Std. Error df t value
## (Intercept) 3.053272e+01 8.404978e-01 7.741354e+02 36.32695
## Age -1.551715e-01 1.843523e-02 9.180688e+02 -8.41712
## SexMen 1.369801e-01 2.004655e-01 6.855194e+02 0.68331
## EF 1.560023e-01 4.541779e-02 1.321175e+03 3.43483
## RaceAfrAm 7.626878e-01 2.151793e-01 7.245358e+02 3.54443
## BMI -1.215142e-01 1.463839e-02 8.184954e+02 -8.30106
## PovStatBelow -3.531219e-01 2.172197e-01 7.169293e+02 -1.62564
## WRATtotal 2.119900e-02 1.526233e-02 7.716566e+02 1.38898
## Age:RaceAfrAm 6.831102e-02 2.315568e-02 8.903722e+02 2.95008
## Age:EF 1.219997e-02 4.556671e-03 1.276193e+03 2.67739
## Pr(>|t|)
## (Intercept) < 2.22e-16
## Age < 2.22e-16
## SexMen 0.49464170
## EF 0.00061130
## RaceAfrAm 0.00041873
## BMI 4.4409e-16
## PovStatBelow 0.10446485
## WRATtotal 0.16524097
## Age:RaceAfrAm 0.00326015
## Age:EF 0.00751503
##
## 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
pAge = seq(-19,20)
hatPhyPerfSingleMN = zMixHat(DanThesisFinal, mm5, vary = "Age=pAge, Race=zQ(AfrAm,White)",fixedCov=c("BMI","Sex","EF","PovStat","WRATtotal"))
par(mar=c(4,4,.5,2),las = 1, lwd = 2)
HNDcolors = HNDpltColors()
## Error in eval(expr, envir, enclos): could not find function "HNDpltColors"
with(hatPhyPerfSingleMN[hatPhyPerfSingleMN$Race == "AfrAm",],plot(pAge,hat, lty = 1, col = "black", type = "l",ylim = c(24,32), ylab = "Time(Sec)", xlab = "Age",xaxt = "n" ))
with(hatPhyPerfSingleMN[hatPhyPerfSingleMN$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")
pAge = seq(-19,20)
hatPhyPerfSingleMN = zMixHat(DanThesisFinal, mm5, vary = "Age=pAge, EF=zQ(-2.306585887,0.138815580,2.584217047)",fixedCov=c("BMI","Sex","Race","EF","PovStat","WRATtotal"))
par(mar=c(4,4,.5,2),las = 1, lwd = 2)
HNDcolors = HNDpltColors()
## Error in eval(expr, envir, enclos): could not find function "HNDpltColors"
with(hatPhyPerfSingleMN[hatPhyPerfSingleMN$EF == "-2.306585887",],plot(pAge,hat, lty = 1, col = "black", type = "l",ylim = c(24,32), ylab = "Time(Sec)", xlab = "Age",xaxt = "n" ))
## Error in xy.coords(x, y, xlabel, ylabel, log): 'x' and 'y' lengths differ
with(hatPhyPerfSingleMN[hatPhyPerfSingleMN$EF == "0.138815580",], lines(pAge,hat, lty = 2, col = "black"))
## Error in xy.coords(x, y): 'x' and 'y' lengths differ
with(hatPhyPerfSingleMN[hatPhyPerfSingleMN$EF == "2.584217047",], lines(pAge,hat, lty = 3, col = "black"))
## Error in xy.coords(x, y): 'x' and 'y' lengths differ
axis(1,at=c(-20,-15,-10,-5,0,5,10,15,20),labels = c("30","35","40","45","50","55","60","65","70"))
## Error in axis(1, at = c(-20, -15, -10, -5, 0, 5, 10, 15, 20), labels = c("30", : plot.new has not been called yet
legend(-20,32, zQ(-2.306585887,0.138815580,2.584217047), lty = 1:2, col = "black",cex=.75,bty="n")
## Error in strwidth(legend, units = "user", cex = cex, font = text.font): plot.new has not been called yet