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Effect size quantification for interrupted time series analysis: implementation in R and analysis for Covid-19 research.

Yael Travis-LumerYair GoldbergStephen Z Levine
Published in: Emerging themes in epidemiology (2022)
For the first time, the effect size in ITS: was quantified, can be estimated by end-users with an R package we developed, and was demonstrated with data showing an increase in mortality following the Covid-19 pandemic. ITS effect size reporting can assist public health policy makers in assessing the magnitude of the entire intervention effect using a single, readily understood measure.
Keyphrases
  • public health
  • healthcare
  • sars cov
  • randomized controlled trial
  • primary care
  • type diabetes
  • mental health
  • cardiovascular events
  • data analysis
  • respiratory syndrome coronavirus