simITS
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) doi:10.48550/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 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.
- Version0.1.1
- R versionunknown
- LicenseGPL-3
- Needs compilation?No
- Last release05/20/2020
Documentation
Team
Luke Miratrix
MDRC
Show author detailsRolesfndBrit Henderson
Show author detailsRolesContributorChloe Anderson
Show author detailsRolesContributorArnold Ventures
Show author detailsRolesfnd
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Last 30 days
This package has been downloaded 125 times in the last 30 days. More than a random curiosity, but not quite a blockbuster. Still, it's gaining traction! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 6 times.
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Last 365 days
This package has been downloaded 1,619 times in the last 365 days. Now we’re talking! This work is officially 'heard of in academic circles', just like those wild research papers on synthetic bananas. The day with the most downloads was Sep 11, 2024 with 24 downloads.
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Dependencies
- Depends2 packages
- Suggests8 packages