Interrupted time series analysis using autoregressive integrated moving average (ARIMA) models: a guide for evaluating large-scale health interventions

BACKGROUND: Interrupted time series analysis is increasingly used to evaluate the impact of large-scale health interventions. While segmented regression is a common approach, it is not always adequate, especially in the presence of seasonality and autocorrelation. An Autoregressive Integrated Moving...

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Detalles Bibliográficos
Autores principales: Schaffer, Andrea L., Dobbins, Timothy A., Pearson, Sallie-Anne
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Technical Advance
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7986567/
https://www.ncbi.nlm.nih.gov/pubmed/33752604
http://dx.doi.org/10.1186/s12874-021-01235-8

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7986567/
https://www.ncbi.nlm.nih.gov/pubmed/33752604
http://dx.doi.org/10.1186/s12874-021-01235-8

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