47 lines
1.7 KiB
R
47 lines
1.7 KiB
R
## File Name: iptw.R
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## File version: 1.0
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#' Compute inverse probability of treatement weights (IPTW) for use with PCM
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#'
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#' This function computes IPTW weights for causal inference with the pcm function
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#'
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#' @param df data.frame containing the data
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#' @param Y string containing the name of the column where the dependent variable is stored in df
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#' @param X vector of strings containing the names of the columns where the independent variables are stored in df
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#' @param target string containing the target causal effect of interest. Either "ate" (average treatment effect, default), "att" (average treatment effect on the treated) or "atu" (average treatment effect on the untreated)
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#' @return A vector of IPT weights
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#' @export
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iptw <- function(df=NULL,Y=NULL,X=NULL,target="ate") {
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if (any(!(Y %in% colnames(df)))) {
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stop("ERROR: provided Y variable name does not exist in df")
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}
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if (!("id"%in%colnames(df))) {
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stop('ERROR: no column named id provided')
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}
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if (target !="ate" & target != "att" & type !="atu")
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dff <- df[,c(Y,X)]
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if (length(X)==1) {
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formu <- paste0(Y,"~",X)
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} else {
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formu <- paste0(Y,"~",X[1])
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for (k in 2:length(X)) {
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xx <- X[k]
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formu <- paste0(formu,"+",xx)
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}
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}
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lr_out <- glm(formula = as.formula(formu),data=df,family = binomial(link = 'logit'))
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if (target == "ate") {
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psw <- df$TT/fitted(lr_out) + (1-df$TT)/(1-fitted(lr_out))
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} else if (target=="att") {
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psw <- rep(NA,nrow(df))
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psw[df[,Y]==1] <- 1
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psw[df[,Y]==0] <- fitted(lr_out)/(1-fitted(lr_out))
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} else if (target=="atu") {
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psw <- rep(NA,nrow(df))
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psw[df[,Y]==0] <- 1
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psw[df[,Y]==1] <- (1-fitted(lr_out))/(fitted(lr_out))
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}
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return(psw)
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}
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