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) <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.

Version: 0.1.1
Depends: dplyr, R (≥ 2.10), rlang
Suggests: arm, ggplot2, knitr, plyr, purrr, rmarkdown, stats, testthat (≥ 2.1.0), tidyr
Published: 2020-05-20
Author: Luke Miratrix [aut, cre], Brit Henderson [ctb], Chloe Anderson [ctb], Arnold Ventures [fnd], MDRC [fnd]
Maintainer: Luke Miratrix <lmiratrix at g.harvard.edu>
License: GPL-3
NeedsCompilation: no
Materials: README
CRAN checks: simITS results

Downloads:

Reference manual: simITS.pdf
Vignettes: Intro simITS
Package source: simITS_0.1.1.tar.gz
Windows binaries: r-devel: simITS_0.1.1.zip, r-release: simITS_0.1.1.zip, r-oldrel: simITS_0.1.1.zip
macOS binaries: r-release (arm64): simITS_0.1.1.tgz, r-release (x86_64): simITS_0.1.1.tgz, r-oldrel: simITS_0.1.1.tgz
Old sources: simITS archive

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