ArticleInternational journal of epidemiology2021
Reflection on modern methods: a common error in the segmented regression parameterization of interrupted time-series analyses.
Article in International journal of epidemiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 66 papers.
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Who cites it
66 citing papers in PubMed, 107 citations in OpenAlex.
- Treatment Patterns in Hospitalized Hip Fracture Patients: An Interrupted Time-Series Analysis Around the New Fee for Secondary Fracture Prevention in Japan.Rheumatology and therapy · 2026Article
- The impact of the UK soft drink industry levy on ethnic inequalities in admission rates for caries-related extractions.Journal of public health (Oxford, England) · 2026Article
- Are We in Control? How Best to Include a Control Group in Interrupted Time Series Designs: A Simulation Study.Journal of evaluation in clinical practice · 2026Article
- The correlation between sanction adjustments and drunk-driving violations and related outcomes in Taiwan: A nationwide interrupted time series analysis.Addiction (Abingdon, England) · 2026Article
- Policy stringency during the COVID-19 pandemic and healthcare services utilization in China: An interrupted time-series analysis.PLoS medicine · 2026Article
- The impact of centralized volume-based procurement policy on dental implant procurement volume in medical institutions of a Western Province in China-a single-group and double-group interruption time series analysis.BMC public health · 2026Article
- Down syndrome birth rate post Dobbs decision: has it changed?Journal of perinatology : official journal of the California Perinatal Association · 2026Article
- Association of Simulation-Based Team Training Implementation with Treatment Process Optimization and Clinical Outcomes in a Chest Pain Center: A Retrospective Pre-Post Analysis of Real-World Data.Journal of multidisciplinary healthcare · 2026Article
- Intimate partner violence victimisation before, during and after the COVID-19 pandemic in Manitoba, Canada: a time series analysis.BMJ public health · 2026Article
- Article
- Effectiveness of the National Immunisation Programme and the catch-up vaccination on the incidence of hepatitis B in China: an interrupted time series analysis from 2005 to 2019.BMJ global health · 2025Article
- Impact of volume-based procurement policy on coronary stent use in tianjin: interrupted time series analysis.Journal of health, population, and nutrition · 2025Article
- Shifting epidemic trends and severity in pediatric Mycoplasma pneumoniae infections in the post-COVID-19 era.Italian journal of pediatrics · 2025Article
- The impact of the SARS-CoV-2 pandemic on umbilical cord blood transplantation in Japan: insights from an interrupted time series analysis.Bone marrow transplantation · 2025Article
- Changing patterns of opioid agonist therapy prescribing in a network of specialised clinics providing care to people with opioid use disorder in Victoria, Australia, 2015 to 2023.Drug and alcohol review · 2025Article
- Interpretation of coefficients in segmented regression for interrupted time series analyses.BMC medical research methodology · 2025Article
- The impact of a comprehensive strategy on HIV treatment continuum in a highly endemic area of China: an interrupted time series analysis.BMC infectious diseases · 2025Article
- The association between the health promotion levy and employment in South Africa: an interrupted time series analysis.BMC nutrition · 2025Article
- Impact of China's National Volume-Based Drug Procurement: A Multilevel Interrupted Time Series Analysis on Medical Expenditures in Hypertensive Patients.International journal of health policy and management · 2025Article
- A mixed methods study protocol evaluating early screening, triaging, risk assessment and health optimisation in perioperative pathways.PloS one · 2025Article
6 more citing papers are in PubMed but not listed here.
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Authors and funding
3 authors at 2 institutions in 3 countries.
Funding
Abstract
Interrupted time-series (ITS) designs are a robust and increasingly popular non-randomized study design for strong causal inference in the evaluation of public health interventions. One of the most common techniques for model parameterization in the analysis of ITS designs is segmented regression, which uses a series of indicators and linear terms to represent the level and trend of the time-series before and after an intervention. In this article, we highlight an important error often presented in tutorials and published peer-reviewed papers using segmented regression parameterization for the analyses of ITS designs. We show that researchers cannot simply use the product between their calendar time variable and the indicator variable indicating pre- versus post-intervention time periods to represent the post-intervention linear segment. If researchers use this often-presented parameterization, they will get an erroneous result for the level change in their time-series. We show that researchers must take care to use the product between their intervention variable and the time elapsed since the start of the intervention, rather than the time since the beginning of their study. Thus, the second linear segment of the time-series indexing the post-intervention level and trend should be zero before intervention implementation and begin by counting from zero, rather than counting from the time elapsed since the beginning of the study. We hope that this article can clarify segmented regression parameterization for the analysis of ITS designs and help researchers avoid confusing and erroneous results in the level changes of their time-series.
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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.