ArticleHealth services & outcomes research methodology
Estimating causal effects: considering three alternatives to difference-in-differences estimation.
Article in Health services & outcomes research methodology. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 57 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
57 citing papers in PubMed, 1 synthesis or guideline pooled it.
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- Evaluation of the Medical Utilization of the Telemedicine Pilot Project for Patients With Diabetes Based on Korean National Health Insurance Claims Data.Journal of Korean medical science · 2026Article
- Adult-use cannabis legalization in the united states: a scoping review of outcome monitoring recommendations.BMC public health · 2025Article
- Difference-in-Differences for Health Policy and Practice: A Review of Modern Methods.Statistics in medicine · 2025Review
- AVERAGED PREDICTION MODELS (APM): IDENTIFYING CAUSAL EFFECTS IN CONTROLLED PRE-POST SETTINGS WITH APPLICATION TO GUN POLICY.The annals of applied statistics · 2025Article
- Considerations for the epidemiological evaluation of hyperlocal interventions: A case study of the New York City overdose prevention centers.Social science & medicine (1982) · 2025Article
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- Effect of the national reimbursement drug list negotiation policy on utilization of negotiated anticancer drugs in Chinese public hospital: a quasi-natural experiment.Frontiers in public health · 2025Article
- Types of Adolescent Screen Use and Positive Wellbeing: Gender and Parental Education Influences.Journal of happiness studies · 2025Article
- The Impact of Devolution on Local Health System Financing: A Synthetic Difference-in-Differences Study of Greater Manchester, England.International journal of health policy and management · 2025Article
- How do family doctors respond to reduced waiting times for cancer diagnosis in secondary care?The European journal of health economics : HEPAC : health economics in prevention and care · 2024Article
- Evaluation of Changes in Prices and Purchases Following Implementation of Sugar-Sweetened Beverage Taxes Across the US.JAMA health forum · 2024Article
- A comparison of quasi-experimental methods with data before and after an intervention: an introduction for epidemiologists and a simulation study.International journal of epidemiology · 2023Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Difference-in-differences (DiD) estimators provide unbiased treatment effect estimates when, in the absence of treatment, the average outcomes for the treated and control groups would have followed parallel trends over time. This assumption is implausible in many settings. An alternative assumption is that the potential outcomes are independent of treatment status, conditional on past outcomes. This paper considers three methods that share this assumption: the synthetic control method, a lagged dependent variable (LDV) regression approach, and matching on past outcomes. Our motivating empirical study is an evaluation of a hospital pay-for-performance scheme in England, the best practice tariffs programme. The conclusions of the original DiD analysis are sensitive to the choice of approach. We conduct a Monte Carlo simulation study that investigates these methods' performance. While DiD produces unbiased estimates when the parallel trends assumption holds, the alternative approaches provide less biased estimates of treatment effects when it is violated. In these cases, the LDV approach produces the most efficient and least biased estimates.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.