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.