Analysis via Simulation of Interrupted Time Series (ITS) Data

Uses simulation to create prediction intervals for post-policy outcomes in interrupted time series (ITS) designs, following Miratrix (2020) . This package provides methods for fitting ITS models with lagged outcomes and variables to account for temporal dependencies. It then conducts inference via simulation, simulating a set of plausible counterfactual post-policy series to compare to the observed post-policy series. This package also provides methods to visualize such data, and also to incorporate seasonality models and smoothing and aggregation/summarization. This work partially funded by Arnold Ventures in collaboration with MDRC.


Reference manual

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0.1.1 by Luke Miratrix, a year ago

Browse source code at

Authors: Luke Miratrix [aut, cre] , Brit Henderson [ctb] , Chloe Anderson [ctb] , Arnold Ventures [fnd] , MDRC [fnd]

Documentation:   PDF Manual  

GPL-3 license

Depends on dplyr, rlang

Suggests arm, ggplot2, knitr, plyr, purrr, rmarkdown, stats, testthat, tidyr

See at CRAN