article Open AccessTop 1% cited
Regression based quasi-experimental approach when randomisation is not an option: interrupted time series analysis
BMJ · 2015 · Vol. 350(jun09 5) · pp. h2750–h2750
Evangelos Kontopantelis✉(University of Manchester)T. Doran(University of York)David A. Springate(University of Manchester)Iain Buchan(University of Manchester)David Reeves(NIHR School for Primary Care Research)
Abstract
Interrupted time series analysis is a quasi-experimental design that can evaluate an intervention effect, using longitudinal data. The advantages, disadvantages, and underlying assumptions of various modelling approaches are discussed using published examples
Healthcare Policy and ManagementPrimary Care and Health OutcomesStatistical Methods and Bayesian InferenceInterrupted Time Series AnalysisInterrupted time seriesTime seriesSeries (stratigraphy)Regression analysisComputer scienceEconometricsRegressionStatisticsMathematics
MeSH terms
Research DesignInterrupted Time Series Analysis
Funding
- National Institute for Health and Care Research
- Medical Research Council
- NIHR School for Primary Care Research
Citations
1,002
FWCI
137.90
field-weighted impact
References
27
Percentile
100%
vs. same field & year
Citations per year
Cited by
Interrupted time series regression for the evaluation of public health interventions: a tutorial
International Journal of Epidemiology · 2016 · 2,967 citations
References
Multilevel and Longitudinal Modeling Using Stata
Biometrics · 2006 · 4,289 citations
Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries
CA A Cancer Journal for Clinicians · 2018 · 87,314 citations
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