calculate_ipw_weights: Propensity Score Weighting for PSsurvival Package

In PSsurvival: Propensity Score Methods for Survival Analysis

Propensity Score Weighting for PSsurvival Package

Description

Functions for calculating propensity score weights with optional trimming for binary and multiple treatment groups. Calculate Inverse Probability Weights (IPW)

Calculates inverse probability weights for binary or multiple treatment groups. For ATE (Average Treatment Effect), weights are 1/e_j(X) for each treatment j. For ATT (Average Treatment Effect on the Treated), weights target a specific treatment group.

Usage

calculate_ipw_weights(
  ps_result,
  data,
  treatment_var,
  estimand = "ATE",
  att_group = NULL
)

Arguments

ps_result	A list returned by estimate_ps(), containing: ps_matrix: Matrix of propensity scores (n x J) for multiple treatments, or NULL for binary treatment ps: Vector of propensity scores for observed treatment n_levels: Number of treatment levels treatment_levels: Vector of treatment level values
data	A data.frame containing the treatment variable.
treatment_var	A character string specifying the name of the treatment variable in data.
estimand	Character string specifying the estimand. One of "ATE" (default) or "ATT" (Average Treatment Effect on the Treated).
att_group	For ATT estimation, specifies which treatment group to target. This is MANDATORY when estimand = "ATT".

Details

For ATE with multiple treatments, weights are:

w_j(X_i) = \frac{1}{e_j(X_i)} \text{ for individual i in treatment j}

For ATT targeting treatment k, weights are:

w_j(X_i) = \begin{cases} 1 & \text{if } j = k \\ \frac{e_k(X_i)}{e_j(X_i)} & \text{if } j \neq k \end{cases}

Value

A numeric vector of IPW weights with length equal to nrow(data).

PSsurvival documentation built on Dec. 9, 2025, 9:07 a.m.