Contents
What can interrupted time series regression be used for?
Interrupted time series (ITS) analysis is a valuable study design for evaluating the effectiveness of population-level health interventions that have been implemented at a clearly defined point in time. It is increasingly being used to evaluate the effectiveness of interventions ranging from clinical therapy to national public health legislation.
How is regression discontinuity used in environmental economics?
Abstract Recent empirical work in several economic \\felds, particularly environmental and energy economics, has adapted the regression discontinuity (RD) framework to applica- tions where time is the running variable and treatment begins at a particular threshold in time.
Which is an example of a discontinuity in time?
An increasingly popular application of the RD design uses time as the running variable, with a treatment date as the threshold. Examples of this egression discontinuity in time” (RDiT) are given in Table 1.
Why are observations remote in time used in rdit?
The use in RDiT of observations remote (in time) from the threshold is a substantial conceptual departure from the identifying assumptions used in a cross-sectional RD, and we show it can lead to bias resulting from unobservable confounders and/or the time-series properties of the data generating process.
When to use intervention analysis in time series?
Intervention analysis in time series refers to the analysis of how the mean level of a series changes after an intervention, when it is assumed that the same ARIMA structure for the series x t holds both before and after the intervention. Suppose that the ARIMA model for x t (the observed series) with no intervention is
How to calculate the effect of an intervention?
Use the data before the intervention point to determine the ARIMA model for the series. Use that ARIMA model to forecast values for the period after the intervention. Calculate the differences between actual values after the intervention and the forecasted values. Examine the differences in step 3 to determine a model for the intervention effect.
What are the four possible patterns of intervention?
Four possible patterns are as follows: Permanent constant change to the mean level: An amount has been added (or subtracted) to each value after time T. Brief constant change to the mean level: There may be a temporary change for one or more periods, after which there is no effect of the intervention.