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Method_new.R
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Method_new.R
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<<<<<<< HEAD
Method_exp1<- function(SimData, model){
Y<-SimData$Y
A<-SimData$A
X1<-SimData$X1
X2<-SimData$X2
X3<-SimData$X3
if(model==1){
PS <- glm(A ~ X1, family = binomial(link = "probit"), data = SimData)
PS <- PS$fitted.values
}else if(model==2){
PS <- glm(A ~ X2, family = binomial(link = "probit"), data = SimData)
PS <- PS$fitted.values
}else if(model==3){
PS <- glm(A ~ X3, family = binomial(link = "probit"), data = SimData)
PS <- PS$fitted.values
}else if(model==4){
PS <- glm(A ~ X1 + X2, family = binomial(link = "probit"), data = SimData)
PS <- PS$fitted.values
}else if(model==5){
PS <- glm(A ~ X1 + X3, family = binomial(link = "probit"), data = SimData)
PS <- PS$fitted.values
}else if(model==6){
PS <- glm(A ~ X2 + X3, family = binomial(link = "probit"), data = SimData)
PS <- PS$fitted.values
}else if(model==7){
PS <- glm(A ~ X1 + X2 +X3, family = binomial(link = "probit"), data = SimData)
PS <- PS$fitted.values
}
bPS<-splines2::bSpline(PS, knots = quantile(PS, names = F)[2:4] ) #bs(PS, knots=quantile(PS, names = F)[2,4])
k<-NCOL(bPS)
colnames(bPS)<- paste0("B",1:k)
SimData<-cbind(SimData,bPS)
output<-glm(formula = Y ~ 1 + B1 + B2 + B3 + B4 +B5 +B6 + A, family=poisson(link=log), data = SimData)
return(output)
}
=======
Method_exp1<- function(SimData, model){
Y<-SimData$Y
A<-SimData$A
X1<-SimData$X1
X2<-SimData$X2
X3<-SimData$X3
if(model==1){
PS <- glm(A ~ X1, family = binomial(link = "probit"), data = SimData)
PS <- PS$fitted.values
}else if(model==2){
PS <- glm(A ~ X2, family = binomial(link = "probit"), data = SimData)
PS <- PS$fitted.values
}else if(model==3){
PS <- glm(A ~ X3, family = binomial(link = "probit"), data = SimData)
PS <- PS$fitted.values
}else if(model==4){
PS <- glm(A ~ X1 + X2, family = binomial(link = "probit"), data = SimData)
PS <- PS$fitted.values
}else if(model==5){
PS <- glm(A ~ X1 + X3, family = binomial(link = "probit"), data = SimData)
PS <- PS$fitted.values
}else if(model==6){
PS <- glm(A ~ X2 + X3, family = binomial(link = "probit"), data = SimData)
PS <- PS$fitted.values
}else if(model==7){
PS <- glm(A ~ X1 + X2 +X3, family = binomial(link = "probit"), data = SimData)
PS <- PS$fitted.values
}
bPS<-splines2::bSpline(PS, knots = quantile(PS, names = F)[2:4] ) #bs(PS, knots=quantile(PS, names = F)[2,4])
k<-NCOL(bPS)
colnames(bPS)<- paste0("B",1:k)
SimData<-cbind(SimData,bPS)
output<-glm(formula = Y ~ 1 + B1 + B2 + B3 + B4 +B5 +B6 + A, family=poisson(link=log), data = SimData)
return(output)
}
>>>>>>> bf47da6a1fdb87610a2366c79e6f55cd26b6b46f