Dan's Thesis Analyses - Tandem Stands
load(file="/Users/meganwilliams/Desktop/UMBC 2016/Dan's Thesis/DanThesisFinal.rdata")
library(lmerTest)
library(zStat)
library(zUtil)
Tandem Stands - Model 1 (Main Effects)
mm1 = lmer(PhyPerfSecsTandem ~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:
## PhyPerfSecsTandem ~ Age + Sex + EF + Race + BMI + PovStat + WRATtotal +
## (1 | HNDid)
## Data: DanThesisFinal
##
## AIC BIC logLik deviance df.resid
## 11066.2 11123.1 -5523.1 11046.2 2184
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -8.8470424 0.0492301 0.1587139 0.2556732 1.3221671
##
## Random effects:
## Groups Name Variance Std.Dev.
## HNDid (Intercept) 1.166993 1.080274
## Residual 7.883594 2.807774
## Number of obs: 2194, groups: HNDid, 1440
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 2.855578e+01 5.552740e-01 9.496915e+02 51.42646 < 2.22e-16
## Age -3.729330e-02 7.290038e-03 9.587300e+02 -5.11565 3.7758e-07
## SexMen 1.251879e-01 1.386240e-01 8.442606e+02 0.90308 0.36674329
## EF 3.177490e-02 3.076066e-02 1.413618e+03 1.03297 0.30179376
## RaceAfrAm 5.082697e-01 1.430297e-01 8.759649e+02 3.55360 0.00040031
## BMI -1.099886e-02 9.110956e-03 1.005114e+03 -1.20721 0.22763426
## PovStatBelow -3.267911e-01 1.445929e-01 8.568473e+02 -2.26008 0.02406678
## WRATtotal 2.230028e-02 1.022655e-02 9.596725e+02 2.18063 0.02945332
##
## Correlation of Fixed Effects:
## (Intr) Age SexMen EF RcAfrA BMI PvSttB
## Age -0.006
## SexMen -0.214 -0.001
## EF 0.264 0.078 -0.019
## RaceAfrAm -0.291 0.007 -0.010 0.115
## BMI -0.502 -0.012 0.182 0.041 -0.015
## PovStatBelw -0.262 0.099 0.042 0.071 -0.040 0.068
## WRATtotal -0.823 -0.006 0.025 -0.403 0.189 -0.017 0.169
Tandem Stands - Model 2 (Two-Way Interactions)
mm2 = lmer(PhyPerfSecsTandem ~(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: PhyPerfSecsTandem ~ (Age + Sex + EF + Race)^2 + BMI + PovStat +
## WRATtotal + (1 | HNDid)
## Data: DanThesisFinal
##
## AIC BIC logLik deviance df.resid
## 11065.0 11156.1 -5516.5 11033.0 2178
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -8.9349110 0.0383872 0.1366044 0.2506094 1.3677948
##
## Random effects:
## Groups Name Variance Std.Dev.
## HNDid (Intercept) 1.046843 1.023153
## Residual 7.939408 2.817695
## Number of obs: 2194, groups: HNDid, 1440
##
## Fixed effects:
## Estimate Std. Error df t value
## (Intercept) 2.844611e+01 5.587617e-01 9.424194e+02 50.90920
## Age -7.486977e-02 1.338070e-02 1.007845e+03 -5.59536
## SexMen 2.206217e-01 2.185069e-01 8.895166e+02 1.00968
## EF 3.124728e-02 4.942738e-02 1.303279e+03 0.63219
## RaceAfrAm 5.409073e-01 1.859986e-01 8.830347e+02 2.90813
## BMI -9.965496e-03 9.165698e-03 9.992068e+02 -1.08726
## PovStatBelow -3.192929e-01 1.439118e-01 8.501840e+02 -2.21867
## WRATtotal 2.393541e-02 1.021049e-02 9.488180e+02 2.34420
## Age:SexMen 1.314334e-02 1.478906e-02 9.373106e+02 0.88872
## Age:EF 5.958437e-03 2.909575e-03 1.287385e+03 2.04787
## Age:RaceAfrAm 4.892379e-02 1.532372e-02 9.665752e+02 3.19268
## SexMen:EF -3.027762e-02 5.630273e-02 1.318793e+03 -0.53776
## SexMen:RaceAfrAm -1.391693e-01 2.836422e-01 8.747071e+02 -0.49065
## EF:RaceAfrAm 2.602045e-02 5.579109e-02 1.307660e+03 0.46639
## Pr(>|t|)
## (Intercept) < 2.22e-16
## Age 2.8364e-08
## SexMen 0.3129240
## EF 0.5273764
## RaceAfrAm 0.0037271
## BMI 0.2771842
## PovStatBelow 0.0267726
## WRATtotal 0.0192735
## Age:SexMen 0.3743813
## Age:EF 0.0407751
## Age:RaceAfrAm 0.0014551
## SexMen:EF 0.5908302
## SexMen:RaceAfrAm 0.6237964
## EF:RaceAfrAm 0.6410135
Tandem Stands - Model 3 (Three-Way Interactions)
mm3 = lmer(PhyPerfSecsTandem~(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: PhyPerfSecsTandem ~ (Age + Sex + EF + Race)^3 + BMI + PovStat +
## WRATtotal + (1 | HNDid)
## Data: DanThesisFinal
##
## AIC BIC logLik deviance df.resid
## 11070.5 11184.3 -5515.2 11030.5 2174
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -8.9457627 0.0408090 0.1390681 0.2486306 1.3876307
##
## Random effects:
## Groups Name Variance Std.Dev.
## HNDid (Intercept) 1.021776 1.010830
## Residual 7.952333 2.819988
## Number of obs: 2194, groups: HNDid, 1440
##
## Fixed effects:
## Estimate Std. Error df t value
## (Intercept) 2.847056e+01 5.592991e-01 9.379686e+02 50.90399
## Age -8.613758e-02 1.612056e-02 1.105158e+03 -5.34334
## SexMen 1.793781e-01 2.255263e-01 9.263360e+02 0.79538
## EF 2.108591e-02 5.557177e-02 1.284165e+03 0.37944
## RaceAfrAm 5.255365e-01 1.865360e-01 8.827217e+02 2.81735
## BMI -9.627524e-03 9.158492e-03 9.923506e+02 -1.05121
## PovStatBelow -3.215935e-01 1.437689e-01 8.446666e+02 -2.23688
## WRATtotal 2.350285e-02 1.020124e-02 9.452259e+02 2.30392
## Age:SexMen 4.303661e-02 2.491322e-02 1.011000e+03 1.72746
## Age:EF 6.247850e-03 5.143013e-03 1.411166e+03 1.21482
## Age:RaceAfrAm 6.723343e-02 2.008960e-02 1.024383e+03 3.34668
## SexMen:EF 1.702246e-03 8.363510e-02 1.380826e+03 0.02035
## SexMen:RaceAfrAm -9.545597e-02 2.869828e-01 8.856989e+02 -0.33262
## EF:RaceAfrAm 4.537671e-02 7.347218e-02 1.271659e+03 0.61760
## Age:SexMen:EF -6.567489e-04 5.903587e-03 1.262742e+03 -0.11125
## Age:SexMen:RaceAfrAm -4.757090e-02 3.129737e-02 9.698763e+02 -1.51996
## Age:EF:RaceAfrAm 3.466708e-04 5.897824e-03 1.326495e+03 0.05878
## SexMen:EF:RaceAfrAm -5.436265e-02 1.124941e-01 1.317374e+03 -0.48325
## Pr(>|t|)
## (Intercept) < 2.22e-16
## Age 1.1077e-07
## SexMen 0.42659897
## EF 0.70442714
## RaceAfrAm 0.00495034
## BMI 0.29341678
## PovStatBelow 0.02555447
## WRATtotal 0.02144319
## Age:SexMen 0.08439036
## Age:EF 0.22463687
## Age:RaceAfrAm 0.00084758
## SexMen:EF 0.98376452
## SexMen:RaceAfrAm 0.73950051
## EF:RaceAfrAm 0.53694701
## Age:SexMen:EF 0.91143915
## Age:SexMen:RaceAfrAm 0.12884580
## Age:EF:RaceAfrAm 0.95313663
## SexMen:EF:RaceAfrAm 0.62899944
Tandem Stands - Model 4 (Four-Way Interactions)
mm4 = lmer(PhyPerfSecsTandem~(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: PhyPerfSecsTandem ~ (Age + Sex + EF + Race)^4 + BMI + PovStat +
## WRATtotal + (1 | HNDid)
## Data: DanThesisFinal
##
## AIC BIC logLik deviance df.resid
## 11072.3 11191.8 -5515.1 11030.3 2173
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -8.9437930 0.0425426 0.1379467 0.2486467 1.3853967
##
## Random effects:
## Groups Name Variance Std.Dev.
## HNDid (Intercept) 1.025628 1.012733
## Residual 7.948010 2.819222
## Number of obs: 2194, groups: HNDid, 1440
##
## Fixed effects:
## Estimate Std. Error df t value
## (Intercept) 2.847275e+01 5.593797e-01 9.394488e+02 50.90058
## Age -8.454472e-02 1.652428e-02 1.157014e+03 -5.11639
## SexMen 1.856200e-01 2.259996e-01 9.221251e+02 0.82133
## EF 2.052454e-02 5.558808e-02 1.289735e+03 0.36923
## RaceAfrAm 5.272827e-01 1.865956e-01 8.816536e+02 2.82580
## BMI -9.675127e-03 9.159880e-03 9.941267e+02 -1.05625
## PovStatBelow -3.203086e-01 1.438138e-01 8.441188e+02 -2.22725
## WRATtotal 2.344678e-02 1.020319e-02 9.461677e+02 2.29799
## Age:SexMen 3.973050e-02 2.602432e-02 1.081155e+03 1.52667
## Age:EF 4.957164e-03 5.917580e-03 1.455627e+03 0.83770
## Age:RaceAfrAm 6.583983e-02 2.033904e-02 1.062181e+03 3.23712
## SexMen:EF 3.836300e-03 8.377554e-02 1.401601e+03 0.04579
## SexMen:RaceAfrAm -1.051610e-01 2.878717e-01 8.798156e+02 -0.36531
## EF:RaceAfrAm 4.669426e-02 7.353615e-02 1.283115e+03 0.63498
## Age:SexMen:EF 2.413314e-03 9.138204e-03 1.479717e+03 0.26409
## Age:SexMen:RaceAfrAm -4.448730e-02 3.207329e-02 1.018681e+03 -1.38705
## Age:EF:RaceAfrAm 2.530649e-03 7.705037e-03 1.339813e+03 0.32844
## SexMen:EF:RaceAfrAm -5.738582e-02 1.127065e-01 1.344360e+03 -0.50916
## Age:SexMen:EF:RaceAfrAm -5.270021e-03 1.197574e-02 1.323745e+03 -0.44006
## Pr(>|t|)
## (Intercept) < 2.22e-16
## Age 3.6434e-07
## SexMen 0.4116712
## EF 0.7120202
## RaceAfrAm 0.0048228
## BMI 0.2911105
## PovStatBelow 0.0261939
## WRATtotal 0.0217800
## Age:SexMen 0.1271360
## Age:EF 0.4023360
## Age:RaceAfrAm 0.0012448
## SexMen:EF 0.9634821
## SexMen:RaceAfrAm 0.7149714
## EF:RaceAfrAm 0.5255522
## Age:SexMen:EF 0.7917468
## Age:SexMen:RaceAfrAm 0.1657295
## Age:EF:RaceAfrAm 0.7426297
## SexMen:EF:RaceAfrAm 0.6107226
## Age:SexMen:EF:RaceAfrAm 0.6599668
Tandem Stands - Model 5 (Retaining significant higher-order terms)
mm5 = lmer(PhyPerfSecsTandem ~Age + Sex + EF + Race + BMI + PovStat + WRATtotal + (1|HNDid) + Age*Race, data=DanThesisFinal,REML=F)
summary(mm5)
## Linear mixed model fit by maximum likelihood t-tests use Satterthwaite
## approximations to degrees of freedom [lmerMod]
## Formula:
## PhyPerfSecsTandem ~ Age + Sex + EF + Race + BMI + PovStat + WRATtotal +
## (1 | HNDid) + Age * Race
## Data: DanThesisFinal
##
## AIC BIC logLik deviance df.resid
## 11060.6 11123.2 -5519.3 11038.6 2183
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -8.8530752 0.0497317 0.1462114 0.2496269 1.3889223
##
## Random effects:
## Groups Name Variance Std.Dev.
## HNDid (Intercept) 1.142964 1.069095
## Residual 7.874576 2.806167
## Number of obs: 2194, groups: HNDid, 1440
##
## Fixed effects:
## Estimate Std. Error df t value
## (Intercept) 2.849522e+01 5.544018e-01 9.462044e+02 51.39814
## Age -6.260015e-02 1.171743e-02 9.758274e+02 -5.34248
## SexMen 1.293486e-01 1.382893e-01 8.429926e+02 0.93535
## EF 2.929904e-02 3.070767e-02 1.412295e+03 0.95413
## RaceAfrAm 4.896796e-01 1.428332e-01 8.696917e+02 3.42833
## BMI -9.838914e-03 9.099022e-03 9.993680e+02 -1.08132
## PovStatBelow -3.104651e-01 1.443566e-01 8.548383e+02 -2.15068
## WRATtotal 2.300531e-02 1.020558e-02 9.570702e+02 2.25419
## Age:RaceAfrAm 4.102854e-02 1.488592e-02 9.594120e+02 2.75620
## Pr(>|t|)
## (Intercept) < 2.22e-16
## Age 1.1412e-07
## SexMen 0.34987673
## EF 0.34018230
## RaceAfrAm 0.00063583
## BMI 0.27981765
## PovStatBelow 0.03178107
## WRATtotal 0.02440975
## Age:RaceAfrAm 0.00595863
##
## Correlation of Fixed Effects:
## (Intr) Age SexMen EF RcAfrA BMI PvSttB WRATtt
## Age 0.028
## SexMen -0.214 -0.009
## EF 0.265 0.072 -0.020
## RaceAfrAm -0.289 0.041 -0.011 0.117
## BMI -0.503 -0.043 0.182 0.040 -0.017
## PovStatBelw -0.264 0.029 0.043 0.070 -0.042 0.070
## WRATtotal -0.824 -0.025 0.025 -0.404 0.188 -0.016 0.170
## Age:RcAfrAm -0.041 -0.784 0.011 -0.030 -0.047 0.046 0.041 0.026
Plot Final Model (mm5)
pAge = seq(-19,20)
hatTandemStand = 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(hatTandemStand[hatTandemStand$Race == "AfrAm",],plot(pAge,hat, lty = 1, col = "black", type = "l",ylim = c(25,35), ylab = "Time(Sec)", xlab = "Age",xaxt = "n" ))
with(hatTandemStand[hatTandemStand$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(-20,35, zQ(AfrAm,White), lty = 1:2, col = "black",cex=.75,bty="n")
