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Learn how to conduct intervention analysis (or interrupted time series analysis) using R and the ARIMA framework. See an example of evaluating a health policy intervention and its impact on medicine dispensing data.
- Chapter 6 Interrupted time series analysis (ITSA) with R: A short ...
Previously, I wrote a tutorial on how to perform an...
- Chapter 6 Interrupted time series analysis (ITSA) with R: A short ...
23 Φεβ 2023 · R Pubs by RStudio. Sign in Register A pragmatic Introduction to Interrupted Time Series; by Chrissy Roberts; Last updated almost 2 years ago; Hide Comments (–) Share Hide Toolbars
MEPS Tutorial 6 - Interrupted Time Series Analysis (ITSA) with R: A Short Tutorial; by Mark Bounthavong; Last updated about 1 year ago; Hide Comments (–) Share Hide Toolbars
Sets up an Interrupted Time Series Analysis (ITSA) for analysing short time series data. define data. Must be a data frame or object coercible into a data frame. define time variable, must either be numeric (such as a year) or of class date. define dependent variable, must be continuous.
This function provides an Interrupted Time Series Analysis (ITSA) model using a variance-centric approach to estimating change in a dependent variable over time.
11 Σεπ 2024 · Interrupted time series should be used when longitudinal data (outcome over time - observations before and after the intervention) full population was affected at one specific point in time (or can be stacked based on intervention)
Previously, I wrote a tutorial on how to perform an interrupted time series analysis (ITSA) in Stata, which is located on my RPubs site . This had me thinking of how to perform an ITSA using R.
