---
title: >-
  DAG With Omitted Objects Displayed (DAGWOOD): a framework for revealing causal
  assumptions in DAGs.
description: >-
  Explore this publication on real-world evidence: DAG With Omitted Objects
  Displayed (DAGWOOD): a framework for revealing causal assumptions in DAGs..
date: '2022-01-01'
category: Publications
tags:
  - University of North Carolina at Chapel Hill
  - Abstract/Manuscript
  - Alexander Breskin
  - Approval & Commercialization
  - 'Yes'
  - R&D
canonical_url: >-
  https://www.headwaterscience.com/resources/publications/acad-university-of-north-carolina-at-chapel-hill/dag-with-omitted-objects-displayed-dagwood-a-framework-for/
source: Headwater
license: © 2026 Headwater. All rights reserved.
slug: dag-with-omitted-objects-displayed-dagwood-a-framework-for
id: 4Xvsm6FCSlbgG3CkEmSjPw
contentType: article
---

## Challenge

Directed acyclic graphs are widely used to represent causal assumptions in epidemiologic research, but the implicit background assumptions and omitted variables in a DAG often go undisclosed, creating opportunities for hidden causal assumptions to bias study design and analysis.

## Solution

Target RWE researchers introduced the DAGWOOD framework—a structured approach for revealing and documenting the causal assumptions typically hidden in conventional DAGs, including omitted common causes, mediators, and selection nodes.

## Use Cases/Links

[Read the publication](https://www.sciencedirect.com/science/article/abs/pii/S1047279722000035)