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.