Unique contribution of SSS to each model (semi-partial correlations)

load(file="~/Desktop/Research/HANDLS Data/MeasurementData1.rdata")
library(ppcor)

## Loading required package: MASS

Make Variables Numeric

##Make Sex Numeric
MeasurementData1$SexNum <- ifelse(MeasurementData1$Sex == "Men",1,0)

##Make Race Numeric
MeasurementData1$RaceNum<- ifelse(MeasurementData1$Race == "White",1,0)

Create Interaction Variables

#Create Interaction Variables
MeasurementData1$RaceNumEduc = (MeasurementData1$RaceNum * MeasurementData1$Educ)

MeasurementData1$RaceNumEmployment01 = (MeasurementData1$RaceNum * MeasurementData1$Employment01)

MeasurementData1$SexNumEmployment01 = (MeasurementData1$SexNum * MeasurementData1$Employment01)

save(MeasurementData1,file="~/Desktop/Research/HANDLS Data/MeasurementData1.rdata")

Unique Contribution of Age to the Model

spcor.test(MeasurementData1$Age0,MeasurementData1$MCLcountry,MeasurementData1[,c("SexNum","RaceNum","Educ","Employment01","acasiIncomx01","Neighborhood02","CES","RaceNumEduc","RaceNumEmployment01", "SexNumEmployment01")])

##        estimate      p.value    statistic    n gp  Method
## 1 0.01920267121 0.3828877898 0.8727739195 2077 10 pearson

Unique Contribution of Race to the Model

spcor.test(MeasurementData1$RaceNum,MeasurementData1$MCLcountry,MeasurementData1[,c("SexNum","Age0","Educ","Employment01","acasiIncomx01","Neighborhood02","CES","RaceNumEduc","RaceNumEmployment01", "SexNumEmployment01")])

##          estimate      p.value     statistic    n gp  Method
## 1 -0.004552770042 0.8361158872 -0.2068903546 2077 10 pearson

Unique Contribution of Education to the Model

spcor.test(MeasurementData1$Educ,MeasurementData1$MCLcountry,MeasurementData1[,c("SexNum","RaceNum","Age0","Employment01","acasiIncomx01","Neighborhood02","CES","RaceNumEduc","RaceNumEmployment01", "SexNumEmployment01")])

##       estimate      p.value    statistic    n gp  Method
## 1 0.0165373147 0.4523797474 0.7515959187 2077 10 pearson

Unique Contribution of Employment to the Model

spcor.test(MeasurementData1$Employment01,MeasurementData1$MCLcountry,MeasurementData1[,c("SexNum","RaceNum","Age0","Educ","acasiIncomx01","Neighborhood02","CES","RaceNumEduc","RaceNumEmployment01", "SexNumEmployment01")])

##        estimate      p.value   statistic    n gp  Method
## 1 0.03009175875 0.1714429525 1.368057396 2077 10 pearson

Unique Contribution of Income to the Model

spcor.test(MeasurementData1$acasiIncomx01,MeasurementData1$MCLcountry,MeasurementData1[,c("SexNum","RaceNum","Age0","Educ","Employment01","Neighborhood02","CES","RaceNumEduc","RaceNumEmployment01", "SexNumEmployment01")])

##         estimate        p.value    statistic    n gp  Method
## 1 -0.06611822886 0.002634148026 -3.011151493 2077 10 pearson

Unique Contribution of Neighborhood to the Model

spcor.test(MeasurementData1$Neighborhood02,MeasurementData1$MCLcountry,MeasurementData1[,c("SexNum","RaceNum","Age0","Educ","Employment01","acasiIncomx01","CES","RaceNumEduc","RaceNumEmployment01", "SexNumEmployment01")])

##         estimate         p.value    statistic    n gp  Method
## 1 -0.07612443563 0.0005324530666 -3.469334118 2077 10 pearson

Unique Contribution of CES to the Model

spcor.test(MeasurementData1$CES,MeasurementData1$MCLcountry,MeasurementData1[,c("SexNum","RaceNum","Age0","Educ","Employment01","acasiIncomx01","Neighborhood02","RaceNumEduc","RaceNumEmployment01", "SexNumEmployment01")])

##       estimate        p.value    statistic    n gp  Method
## 1 -0.203846682 7.92960645e-21 -9.461929985 2077 10 pearson

Unique Contribution of Race*Education Interaction to the Model

spcor.test(MeasurementData1$RaceNumEduc,MeasurementData1$MCLcountry,MeasurementData1[,c("SexNum","RaceNum","Age0","Educ","Employment01","acasiIncomx01","Neighborhood02","CES","RaceNumEmployment01", "SexNumEmployment01")])

##        estimate      p.value    statistic    n gp  Method
## 1 0.01245258151 0.5715113779 0.5659174637 2077 10 pearson

Unique Contribution of Race*Employment Interaction to the Model

spcor.test(MeasurementData1$RaceNumEmployment01,MeasurementData1$MCLcountry,MeasurementData1[,c("SexNum","RaceNum","Age0","Educ","Employment01","acasiIncomx01","Neighborhood02","CES","RaceNumEduc", "SexNumEmployment01")])

##         estimate      p.value     statistic    n gp  Method
## 1 -0.01936128945 0.3789693354 -0.8799859146 2077 10 pearson

Unique Contribution of Sex*Employment Interaction to the Model

spcor.test(MeasurementData1$SexNumEmployment01,MeasurementData1$MCLcountry,MeasurementData1[,c("SexNum","RaceNum","Age0","Educ","Employment01","acasiIncomx01","Neighborhood02","CES","RaceNumEduc","RaceNumEmployment01")])

##         estimate      p.value    statistic    n gp  Method
## 1 -0.02821064758 0.1998230548 -1.282466315 2077 10 pearson

Unique Contribution of Sex to the Model

spcor.test(MeasurementData1$SexNum,MeasurementData1$MCLcountry,MeasurementData1[,c("CES","RaceNum","Age0","Educ","Employment01","acasiIncomx01","Neighborhood02","RaceNumEduc","RaceNumEmployment01", "SexNumEmployment01")])

##        estimate     p.value   statistic    n gp  Method
## 1 0.02669664817 0.225043547 1.213588869 2077 10 pearson