propensity: Estimating propensity scores

In ivmte: Instrumental Variables: Extrapolation by Marginal Treatment Effects

Description

This function estimates the propensity of taking up treatment. The user can choose from fitting a linear probability model, a logit model, or a probit model. The function can also be used to generate a table of propensity scores for a given set of covariates and excluded variables. This was incorporated to account for the LATE being a target parameter. Specifically, if the argument formula is the name of a variable in data, but the target parameter is not the LATE, then no propensity model is returned. If the target parameter is the LATE, then then the propensity model is simply the empirical distribution of propensity scores in the data conditioned on the set of covariates declared in late.X and late.Z.

Usage

propensity(formula, data, link = "logit", late.Z, late.X, env = parent.frame())

Arguments

formula	Formula characterizing probability model. If a variable in the data already contains the propensity scores, input the variable as a one-sided formula. For example, if the variable pz contains the propensity score, input formula = ~ pz.
data	data.frame with which to estimate the model.
link	Link function with which to estimate probability model. Can be chosen from "linear", "logit", or "probit".
late.Z	A vector of variable names of excluded variables. This is required when the target parameter is the LATE.
late.X	A vector of variable names of non-excluded variables. This is required when the target parameter is the LATE, and the estimation procedure will condition on these variables.
env	environment, the environment for the original propensity score formula.

Value

A vector of propensity scores for each observation, as well as a 'model'. If the user inputs a formula characterizing the model for taking up treatment, then the lm/glm object is returned. If the user declares a variable in the data set to be used as the propensity score, then a data.frame containing the propensity score for each value of the covariates in the probability model is returned.

Examples

dtm <- ivmte:::gendistMosquito()

## Declaring a probability model.
propensity(formula = d ~ z,
               data = dtm,
               link = "linear")

## Declaring a variable to be used instead
propensity(formula = ~ pz,
               data = dtm,
               link = "linear")

ivmte documentation built on Sept. 17, 2021, 5:06 p.m.