cali_mean_ybinary_algm: Calibrate Estimate of Intervention Mean for Binary Outcome

In JiajingZ/CopSens: Copula-Based Sensitivity Analysis for Observational Causal Inference

Calibrate Estimate of Intervention Mean for Binary Outcome

Description

Calibrate Estimate of Intervention Mean for Binary Outcome

Usage

cali_mean_ybinary_algm(i, gamma, mu_u_tr, mu_u_t, mu_y_t, nsim = 4000)

Arguments

i	Observation index.
gamma	Scalar or vector specifying the sensitivity parameters.
mu_u_tr	Matrix of conditional confounder means for all observed treatments with latent variables in columns.
mu_u_t	Matrix of conditional confounder means for treatments of interest with latent variables in columns.
mu_y_t	Scalar or vector that contains naive estimates of treatment effects ignoring confounding.
nsim	Number of simulation sample draws.

Value

Scalar of calibrated intervention mean.

JiajingZ/CopSens documentation built on May 2, 2023, 6:45 a.m.