ArticleStatistics in medicine2023
In praise of Prais-Winsten: An evaluation of methods used to account for autocorrelation in interrupted time series.
Article in Statistics in medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.
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Who cites it
34 citing papers in PubMed.
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- Temporal Trends in Needlestick and Sharp Injury Incidence Rates During the COVID-19 Pandemic in a Tertiary Care Hospital in Korea.Journal of Korean medical science · 2026Article
- its2s: a Python package for two-stage interrupted time series analysis using machine learning.medRxiv : the preprint server for health sciences · 2026Article
- Impact of National Policies Promoting Appropriate Antibiotic Use on Outpatient Prescriptions and Hospitalizations for Bacterial Complications of Acute Respiratory Infections in Japan: An Interrupted Time-Series Analysis.Open forum infectious diseases · 2026Article
- Universal Free Contraception Coverage Policy, Out-of-Pocket Payments, and Costs.JAMA health forum · 2026Article
- Where are we going for the treatment in ischaemic stroke: a comprehensive study of investigator-sponsored randomised controlled trials, 1990-2024.Stroke and vascular neurology · 2026Observational
- Evaluating the Effect of Diagnosis-Intervention Packet (DIP) Reform in China on Hospitalization Outcomes for Patients with Chronic Obstructive Pulmonary Disease with Special Reference to M City.Healthcare (Basel, Switzerland) · 2026Article
- Effect of a financial incentive scheme on promoting prescription of biosimilars: a interrupted time-series analyses.Annals of clinical epidemiology · 2026Article
- Spatiotemporal dynamics of waterborne and foodborne disease outbreaks in Brazil: regional inequality analysis and risk area mapping to inform public health strategies.BMC public health · 2026Article
- Evaluation of statistical methods in R for estimating intervention effects using segmented linear regression in the AB interrupted time series design.BMC medical research methodology · 2026Article
- Incidence, mortality, and management of status epilepticus from 2012 to 2022: An 11-year nationwide study.Epilepsia · 2026Article
- Effect of educational intervention on polypharmacy management among community pharmacists: An interrupted time series analysis.Annals of clinical epidemiology · 2026Article
- Temporal trend of violence due to neglect/abandonment in older women in Brazil (2009-2022).Revista brasileira de enfermagem · 2026Article
- Impact of a tailored, department-specific antimicrobial stewardship team intervention based on AWaRe guidelines: a single-center, cohort, interrupted-time series study.Journal of pharmaceutical health care and sciences · 2025Article
- Interrupted Time Series Analysis in Environmental Epidemiology: A Review of Traditional and Novel Modeling Approaches.Current environmental health reports · 2025Review
- Article
- Impact of Regulatory Post-Market Safety Advisories on Prescribing Practices: An Interrupted Time Series Analysis.Clinical pharmacology and therapeutics · 2025Article
- Trends and Geographical Distribution of Family Health Strategy in Brazil from 2009-2023.Healthcare (Basel, Switzerland) · 2025Article
- Impact of Health All-in-One Machines on access to healthcare of rural areas in China: an interrupted time series analysis.BMC health services research · 2025Article
- Impact of increasing CD4 count threshold eligibility for antiretroviral therapy initiation on advanced HIV disease and tuberculosis prevalence and incidence in South Africa: an interrupted time series analysis.BMJ global health · 2025Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
Interrupted time series are increasingly being used to assess the population impact of public health interventions. These data are usually correlated over time (auto correlated) and this must be accounted for in the analysis. Typically, this is done using either the Prais-Winsten method, the Newey-West method, or autoregressive-moving-average (ARMA) modeling. In this paper, we illustrate these methods via a study of pneumococcal vaccine introduction and explore their performance under 20 simulated autocorrelation scenarios with sample sizes ranging between 20 and 300. We show that in terms of mean square error, the Prais-Winsten and ARMA methods perform best, while in terms of coverage the Prais-Winsten method generally performs better than other methods. All three methods are unbiased. As well as having good statistical properties, the Prais-Winsten method is attractive because it is decision-free and produces a single measure of autocorrelation that can be compared between studies and used to guide sample size calculations. We would therefore encourage analysts to consider using this simple method to analyze interrupted time series.
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