calculate_overlap_weights: Calculate Overlap Weights

In PSsurvival: Propensity Score Methods for Survival Analysis

Calculate Overlap Weights

Description

Calculates overlap weights using the Li & Li (2019) formula for binary or multiple treatment groups. Overlap weights target the population with the most equipoise and are bounded between 0 and 1.

Usage

calculate_overlap_weights(ps_result, data, treatment_var)

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.

Details

For multiple treatments, overlap weights are calculated as:

w_j(X_i) = \frac{1/e_j(X_i)}{\sum_{l=1}^{J} 1/e_l(X_i)}

For binary treatment (J=2), this reduces to:

w(X) = 1 - P(Z = observed | X)

which equals the probability of receiving the opposite treatment.

Value

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

References

Li, F., & Li, F. (2019). Propensity score weighting for causal inference with multiple treatments. The Annals of Applied Statistics, 13(4), 2389-2415.

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