Yael-Travis-Lumer/its2es: Interuppted Time Series Analysis and Corresponding Effect Sizes

This package implements interrupted time series analysis for both continuous and count outcomes, and quantifies the associated effect size, as described in Effect Size Quantification for Interrupted Time Series Analysis: Implementation in R for Covid-19 Research. The main functions fit an ITS regression model, and then use the fitted values and the model-based counterfactual values to quantify the effect size (Cohen's d for continuous outcomes and relative risk for count outcomes).

install.packages("remotes")
remotes::install_github("Yael-Travis-Lumer/its2es")