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.

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

Documentation:

Reference manual:	simITS.pdf
Vignettes:	Intro simITS

Downloads:

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-oldrel (arm64): simITS_0.1.1.tgz, r-release (x86_64): simITS_0.1.1.tgz, r-oldrel (x86_64): simITS_0.1.1.tgz
Old sources:	simITS archive

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