fusion: Balancing Weights for Data-Fusion

In kevjosey/cbal: Covariate Balancing Weights using Generalized Projections of Bregman Distances

Balancing Weights for Data-Fusion

Description

The fusion_ATE() function finds balancing weights for combining datasets to estimate the target population average treatment effect. This function requires complete individual-level data from both samples whereas the transport function only requires complete data from the study sample and covariate data from the target sample.

Usage

fusion_ATE(
  S,
  X,
  Y,
  Z,
  base_weights = NULL,
  optim_ctrl = list(maxit = 500, reltol = 1e-10),
  ...
)

Arguments

S	the binary vector of sample indicators.
X	the balance functions to be contrained.
Y	the observed responses.
Z	the binary treatment assignment.
base_weights	a vector of optional base weights with length equal to the number of rows in X.
optim_ctrl	a list of arguments that will be passed to optim().
...	additional arguments.

References

Josey KP, Yang F, Ghosh D, Raghavan S (2020). "A Calibration Approach to Transportability and Data-Fusion with Observational Data." arXiv:2008.06615 [stat].

kevjosey/cbal documentation built on July 22, 2023, 11:04 a.m.