#探索的因子分析
> x<-read.delim("clipboard")
> factanal(x,factors=8,rotation="varimax")

#確認的因子分析
> x<-read.delim("clipboard")
> consumer.model.cfa<-'
+ f1=~active1+active2+active3
+ f2=~fTV1+fTV2+fTV3
+ f3=~fmagazine1+fmagazine2+fmagazine3
+ f4=~fLIVE1+fLIVE2+fLIVE3
+ f5=~fradio1+fradio2+fradio3
+ f6=~faudition1+faudition2+faudition3
+ f7=~fSNS1+fSNS2+fSNS3
+ f8=~fyoutube1+fyoutube2+fyoutube3'
> library(lavaan)
> fit<-cfa(model=consumer.model.cfa,data=x,estimator="ML")
> summary(fit,fit.measures=TRUE,standardized=T,rsquare=T)

#共分散構造分析
> x<-read.delim("clipboard")
> first.model.sem<-'
+ f1=~active1+active2+active3
+ f2=~fTV1+fTV2+fTV3
+ f3=~fmagazine1+fmagazine2+fmagazine3
+ f4=~fLIVE1+fLIVE2+fLIVE3
+ f5=~fradio1+fradio2+fradio3
+ f6=~faudition1+faudition2+faudition3
+ f7=~fSNS1+fSNS2+fSNS3
+ f8=~fyoutube1+fyoutube2+fyoutube3
+ f1~f2
+ f1~f3
+ f1~f4
+ f1~f5
+ f1~f6
+ f1~f7
+ f1~f8'
> library(lavaan)
> fit<-sem(model=first.model.sem,data=x,estimator="ML")
> summary(fit,fit.measures=TRUE,standardized=T,rsquare=T)

#コンジョイント分析
 experiment<-expand.grid(
+ gentei=c("あり","なし"),
+ hindo=c("多い","少ない"),
+ offshot=c("あり","なし"),
+ SNS=c("あり","なし"))
> design<-caFactorialDesign(data=experiment,type="orthogonal")
> design
> caEncodedDesign(design)
> cor(caEncodedDesign(design))
> x<-read.delim("clipboard")
> tprefm<-x
> tprof<-caEncodedDesign(design)
> tlevn<-as.matrix(c("あり","なし","多い","少ない","あり","なし","あり","なし"))
> Conjoint(tprefm,tprof,tlevn)