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Questions tagged [intervention-analysis]

Intervention analysis estimates the effect of an external intervention on a time-series.

Intervention analysis estimates the effect of an external or exogenous intervention (e.g. the introduction of new regulations) on a time-series. Intervention analysis tests the causal hypothesis that the slope or intercept of the time-series is different after the intervention, or seeks to estimate the magnitude of intervention effects. Intervention analysis is useful when a randomized trial is not possible.

Intervention analysis is typically conducted with the Box & Jenkins ARIMA framework, using the methods outlined by Box & Tiao (1965) ‘A Change in Level of a Non-Stationary Time Series’, Biometrika 52, no. 1: 181–192. However, other methods such as segmented regression may be used.

Intervention analysis is sometimes called interrupted time-series analysis.

Analysis of time series seeking to detect a possible exogenous intervention of unknown time may make use of regime switching or change point analysis.

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ARIMA Intervention Transfer Function - How to Visualize the Effect

I have a monthly time series with an intervention and I would like to quantify the effect of this intervention on the outcome. I realize the series is rather short and the effect is not yet concluded. The Data cds <- structure(c(2580L, 2263L, 3679L,…
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Intervention analysis with multi-dimensional time-series

I would like to do an intervention analysis to quantify the results of a policy decision on the sales of alcohol over time. I am fairly new to time series analysis, however, so I have some beginners questions. An examination of the literature…
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Difference-in-Differences Estimator for Logistic Regressions

I have a pre-post intervention study with four groups: 1) Pre-Intervention Control, 2) Pre-Intervention Treatment, 3) Post-Intervention Control, and 4) Post-Intervention Treatment. The outcome is a binary variable. There four other predictor…
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Intervention With Differencing

When conducting an intervention analysis with time series data (aka Interrupted Time series) as discussed here for example one requirement I have is to estimate the total gain (or loss) due to the intervention - i.e. number of units gained or lost…
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Arimax Prediction : Using Forecast Package

The arimax function in the TSA package is to my knowledge the only R package that will fit a transfer function for intervention models. It lacks a predict function though which is sometimes needed. Is the following a work-around for this issue,…
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Using Google Causal Impact package to assess the significance of a planned intervention

I am using the Causal Impact package in R to infer the causal effect of an intervention in some data which are highly correlated and seasonal. Specifically, i got 17 days of hourly data, intervetion happening in the end of day 13. I have two…
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Intervention Analysis Coding in R TSA Package

I am studying intervention analysis in time series with the Cryer and Chan book and am looking at trying to understand how to code the step response interventions. One question I had is how to differentiate between these two models: It appears the…
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Intervention Analysis - Pulse over several periods

I have a couple weekly time series and an intervention occurred over several weeks and then for some, after a period of no intervention, began again. So, the pattern is off for a period of weeks, then on for a period of weeks, then off for a period…
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What test should I use to determine if a policy change had a statistically significant impact on website registrations?

A client's website was operating under a certain policy for membership sign ups for over a year. At the start of October 2012 the client implemented a new policy for sign ups that was supposed to encourage more registrations. This policy was applied…
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Interrupted Time Series Analysis with multiple Intervention timepoints

I was wondering if it is possible to do a interrupted time series analysis with an intervention that is introduced and removed at specific intervals throughout the time-series. All of the literature I am reading is saying that for a time-series…
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How to interpret coefficients in a regression with ARIMA errors?

I've got some time-series business data that I can fit relatively well with a ARIMA(2,1,0)(1,1,0)[12] model (using R's excellent forecast::Arima -- thanks Prof. Hyndman!). The series is dominated by seasonal effects, but has trends as well, thus the…
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Test for the significance of the effect of an intervention in a time series

I am looking for the best approach to test for the significance of the effect of an intervention that occurred at a known time on a time series data. Using a toy dataset as an example, I have come up with two approaches. Data y <- c(rnorm(10, 10,…
Mihael
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Interrupted time-series analysis for panel data

I am familiar with using regression with ARIMA errors to model interrupted time-series, in order to estimate the change in magnitude caused by a policy intervention. These models seem to be designed for a single time series, and thus if multiple…
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Intervention analysis in time-series regression with seasonal ARIMA errors

Intervention analysis in Box-Jenkins framework crosspoinds to time-series regression with arma errors if the noise is stationary or arima errors if the noise is non-stationary. For a seasonal time series data with increasing trend, the noise model…
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Measuring length of intervention effect

I ran a study in which participants were randomized to either a control or an intervention, with outcomes in the form of time-to-event data. While overall time-to-event is shorter in the intervention group than in the control group (log-rank test $p…
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