Causal interaction and effect modification
Same Model, Different Concepts
Bibliographic Data
| ID | 6342247 |
|---|---|
| Authors | Luke Keele (0000-0002-3859-2713, University of Pennsylvania, corresponding author), Randolph T Stevenson (0000-0003-2565-1355, Rice University) |
| Year | 2021 |
| Volume | 9 |
| Issue | 3 |
| Pages | 641-649 |
| Publication date | 2021-07-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Political Science Research and Methods (JOURNAL) |
| Journal identifiers | ISSN: 2049-8470 • E-ISSN: 2049-8489 |
| Publisher | Cambridge University Press (CUP) (PUBLISHER) |
| DOI | 10.1017/psrm.2020.12 |
| OpenAlex | W3017577476 |
| Language | EN |
| Citations received | 18 |
| References cited | 17 |
Social scientists use the concept of interactions to study effect dependency. In the causal inference literature, interaction terms may be used in two distinct type of analysis. The first type of analysis focuses on causal interactions, where the analyst is interested in whether two treatments have differing effects when both are administered. The second type of analysis focuses on effect modification, where the analyst investigates whether the effect of a single treatment varies across levels of a baseline covariate. While both forms of interaction analysis are typically conducted using the same type of statistical model, the identification assumptions for these two types of analysis are very different. In this paper, we clarify the difference between these two types of interaction analysis. We demonstrate that this distinction is mostly ignored in the political science literature. We conclude with a review of several applications where we show that the form of the interaction is critical to proper interpretation of empirical results
Causal inference · Cognitive psychology · Covariate · Dependency (UML · Econometrics · Identification (biology · Inference · Interaction · Interpretation (philosophy · Statistics · Type (biology · Advanced Causal Inference Techniques · Computer Science · Electoral Systems and Political Participation · Mathematics · Psychology · Qualitative Comparative Analysis Research · Artificial Intelligence
Quantities of Interest for Interactions and the Pitfalls of Assuming Linear Treatment Effects
Occupational labor markets, skills, and immigration concerns
“The mother of all political problems”? On asylum seekers and elections
The Impact of State Principal Evaluation Policies on Equity for Economically Disadvantaged Students
La percepción de desigualdad económica y su influencia sobre la justificación de las diferencias de ingreso legítimas
Statistical evidence, discrimination, and causation
The “Women’s Representation-Corruption Link” and Environmentalism
Does the military lose public confidence without compliance with civilian control? Experimental evidence from Japan
Like parent, like child
Precolonial and Colonial Origins of Inclusive Peace
Government–Opposition Relations and the Vote of No-Confidence
Online Abuse of Politicians
Do immigrants at bay keep the xenophobes away? Post-entry rights and public opposition to immigrant admission
Citizens’ perceptions of online abuse directed at politicians
More Equality for Women Does Mean Less War
The Mental Health of Female and Male Homemakers
Credibility and/or anxiety - The moderators of political information on migration
Shelter from the storm
Counterfactuals and Causal Inference
Graphical Causal Models
The Consquences of Adjustment for a Concomitant Variable That Has Been Affected by the Treatment
Causal inference in statistics
Money, Reputation, and Incumbency in U.S. House Elections, or Why Marginals Have Become More Expensive
A Simple Multivariate Test for Asymmetric Hypotheses
How Conditioning on Posttreatment Variables Can Ruin Your Experiment and What to Do about It
Improving Tests of Theories Positing Interaction
Understanding Interaction Models
How Much Should We Trust Estimates from Multiplicative Interaction Models? Simple Tools to Improve Empirical Practice
Hypothesis Testing and Multiplicative Interaction Terms
Modeling and Interpreting Interactive Hypotheses in Regression Analysis
What Triggers Public Opposition to Immigration? Anxiety, Group Cues, and Immigration Threat
Explaining Causal Findings Without Bias
The Returns to Office in a "Rubber Stamp" Parliament
| Unique citing works | 18 |
|---|---|
| Citations per year | 3,6 |
| Citation span | 2021 - 2026 (6) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 18 |