Analysis via Simulation of Interrupted Time Series (ITS) Data R package simITS version 0.1.1 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. Software Depends: dplyr, R (>= 2.10), rlang Suggests: arm, ggplot2, knitr, plyr, purrr, rmarkdown, stats, testthat (>= 2.1.0), tidyr Luke Miratrix <lmiratrix@g.harvard.edu> Comprehensive R Archive Network (CRAN) Luke Miratrix [aut, cre], Brit Henderson [ctb], Chloe Anderson [ctb], Arnold Ventures [fnd], MDRC [fnd] GPL-3 2020-05-20 application/tgz https://CRAN.R-project.org/package=simITS doi:10.32614/CRAN.package.simITS