Causal Mediation and Sensitivity Analysis for Mixed-Scale Data

11/06/2021
by   Lexi Rene, et al.
0

The goal of causal mediation analysis, often described within the potential outcomes framework, is to decompose the effect of an exposure on an outcome of interest along different causal pathways. Using the assumption of sequential ignorability to attain non-parametric identification, Imai et al. (2010) proposed a flexible approach to measuring mediation effects, focusing on parametric and semiparametric normal/Bernoulli models for the outcome and mediator. Less attention has been paid to the case where the outcome and/or mediator model are mixed-scale, ordinal, or otherwise fall outside the normal/Bernoulli setting. We develop a simple, but flexible, parametric modeling framework to accommodate the common situation where the responses are mixed continuous and binary, and apply it to a zero-one inflated beta model for the outcome and mediator. Applying our proposed methods to a publicly-available JOBS II dataset, we (i) argue for the need for non-normal models, (ii) show how to estimate both average and quantile mediation effects for boundary-censored data, and (iii) show how to conduct a meaningful sensitivity analysis by introducing unidentified, scientifically meaningful, sensitivity parameters.

READ FULL TEXT

page 23

page 24

research
10/19/2020

Causal Inference for Nonlinear Outcome Models with Possibly Invalid Instrumental Variables

Instrumental variable methods are widely used for inferring the causal e...
research
03/09/2023

Sensitivity analysis for principal ignorability violation in estimating complier and noncomplier average causal effects

An important strategy for identifying principal causal effects, which ar...
research
10/15/2022

Heterogeneous interventional indirect effects with multiple mediators: non-parametric and semi-parametric approaches

We propose semi- and non-parametric methods to estimate conditional inte...
research
11/01/2018

Exact parametric causal mediation analysis for non-rare binary outcomes with binary mediators

In this paper, we derive the exact parametric expressions of natural dir...
research
01/30/2021

Bayesian Cumulative Probability Models for Continuous and Mixed Outcomes

Ordinal cumulative probability models (CPMs) – also known as cumulative ...
research
01/20/2020

Non-linear Mediation Analysis with High-dimensional Mediators whose Causal Structure is Unknown

With multiple potential mediators on the causal pathway from a treatment...
research
09/16/2019

Novel Methods for the Analysis of Stepped Wedge Cluster Randomized Trials

Stepped wedge cluster randomized trials (SW-CRTs) have become increasing...

Please sign up or login with your details

Forgot password? Click here to reset