#Chapter 6 Script

#creating scatterplots

library (car) #this activates the car library, which has the scatterplot command
scatterplot (proneng~aoa, data=flegeetal1999)

#modyfying a scatterplot in r console

scatterplot(PronEng~AOA, reg.line=lm, smooth=TRUE, labels=FALSE,
boxplots='xy', span=0.5, xlab="Age of arrival", ylab="Pronunciation
score", cex=1.6, data=flegeetal1999)

#Viewing Simple Scatterplot Data by Categories

dekeyser$Status<-factor(dekeyser$Status)


scatterplot(GJTScore~Age | Status, by.groups=TRUE, data=dekeyser)

#multiple scatterplots

library (car)
scatterplot.matrix(~age+aptscore+useeng, reg.line=lm, smooth=TRUE, span=0.5,
diagonal = 'density', data=larsonhall2008)


#calculating correlation coefficients

library(Hmisc, pos=4)
rcorr.adjust(larsonhall2008[,c("aptscore","gjtscore","totalhrs")],
type="pearson")

cor.test(larsonhall2008$gjtscore, larsonhall2008$aptscore,
method="kendall")


#robust correlation

library(mvoutlier)
attach(dekeyser)
cor.plot(Age,GJTScore)

library(MASS)
cov.rob(cbind(Age,GJTScore),cor=T) #notice that the variables get bound together using
#cbind()
detach(dekeyser)

cor(AGE, GJTSCORE, method="spearman")


#partial correlation

partial.cor(partial[,c("age","LOR","aptitude")], use="complete.obs")

#point-biserial correlations and inter-rater reliability

reliability(cov(LHtest[,c("Q43","Q44","Q45","TotalScore")],
use="complete.obs"))

#inter-rater reliability

reliability(cov(MDM[,c("m001","m002","m003","m004","m005","m006","m007",
"m008","m009","m010")], use="complete.obs"))


rcorr.adjust(MDM[c("m001","m002","m003","m004","m005","m006","m007","m008",
"m009","m010")],type="pearson")


library(psych)
alpha(LHtest)


rcorr.adjust(MDM[c("m001","m002","m003","m004","m005")],type="pearson")