Uses simulation to create prediction intervals for postpolicy outcomes in interrupted time series (ITS) designs, following Miratrix (2020) <arXiv:2002.05746>. 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 postpolicy series to compare to the observed postpolicy 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.
Package details 


Author  Luke Miratrix [aut, cre], Brit Henderson [ctb], Chloe Anderson [ctb], Arnold Ventures [fnd], MDRC [fnd] 
Maintainer  Luke Miratrix <lmiratrix@g.harvard.edu> 
License  GPL3 
Version  0.1.1 
Package repository  View on CRAN 
Installation 
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