meas_effect_uncond: Compute estimates of the unconditional association measures

In FrankLef/fciR: Data and functions used with Fundamentals of Causal Inference by Babette Brumback

Compute estimates of the unconditional association measures

Description

Compute estimates of the unconditional association measures.

Usage

meas_effect_uncond(data, formula = Y ~ T)

bootu(data, formula = Y ~ T)

Arguments

data	Dataframe of raw data.
formula	The model formula.

Details

Compute estimates of the unconditional association measures, hence the u in bootu(), and their confidence intervals. 1- We use Gaussian, Poisson and Binomial glm to solve the estimating equations of the measures, not their distributions 2- The association measures' distributions (ci) are estimated by bootstrapping Assumptions: We assume that (3.2) holds but not (3.1) See p. 45 and 46 for more details.

Value

Dataframe in a useable format for rsample::bootstraps.

Source

Section 3.3

FrankLef/fciR documentation built on Nov. 12, 2023, 6:09 a.m.