Nothing
InterUplift <- function(data, ...) UseMethod("InterUplift")
InterUplift.default <- function(data, treat, outcome, predictors, input = "all", ...){
# Interaction estimator.
#
# Args:
# data: a data frame containing the treatment, the outcome and the predictors.
# treat: name of a binary (numeric) vector representing the treatment
# assignment (coded as 0/1).
# outcome: name of a binary response (numeric) vector (coded as 0/1).
# predictors: a vector of names representing the predictors to consider in the model.
# input: controls if we want to use all the predictors ("all")
# or the output of BestFeatures() function as predictors ("best")
#
# Returns:
# Fitted interaction estimator model.
# Error handling
if (input != "all" & input != "best"){
stop("Choose an appropriate method for input in 'all' or 'best'")
}
if (input == "all") {
inter_formula <- c()
for (k in seq(1:length(predictors))) {
inter_formula <- paste(inter_formula, paste(predictors[k], treat, sep = ":"), sep="+")
}
model_formula <- as.formula(paste(paste(outcome, "~", treat, "+"),paste(predictors,collapse="+"),inter_formula))
model <- glm(model_formula, family=binomial(link="logit"), data, ...)
}
if (input == "best") {
model_formula <- as.formula(paste(paste(outcome, "~"),paste(predictors,collapse = "+")))
model <- glm(model_formula, family=binomial(link="logit"), data, ...)
}
cl <- match.call()
cl[[1]] <- as.name("InterUplift")
model$call <- cl
class(model) <- c("InterUplift", "glm", "lm")
return(model)
}
# END FUN
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