st: Interrupted Time Series Analysis

["Ward Vanlaar" <wardv@tirf.ca>]

Hi all,

A while ago a question was asked about interrupted time series analysis. The thread of emails is indexed under the title "Interrupted Time Series Analysis". Pursuant to this thread of messages, I have a follow-up question. 

I am using ARIMA time series modeling in Stata to model the intervention effect of a road safety program in a particular jurisdiction. I am using a dummy variable to distinguish between months before the program was implemented versus months when the program was in place to model the intervention and to see whether a significant change took place after the implementation of the program (for example a significant decrease in road crashes due to the safety program). Effectively, this is enables me to model a "sudden permanent" intervention, i.e., an immediate effect that remains over time. However, I also want to model a "gradual permanent model" (instead of a sudden change the change is gradual and remains over time, modeled as ω/(1-δ), where the first parameter in the numerator ω represents the intervention effect and the second parameter in the denominator δ quantifies how quickly a stable impact was realized during subsequent months) and a "sudden temporary model"  (there !
 is an immediate effect, a spike, but the effect also immediately disappears, also modeled as ω/(1-δ), but this now represents the total displacement of the series level).

The previous thread ended by stating that an alternative for transfer functions exists in Stata using covariates with ARMAX.

I would appreciate it if someone can elaborate on either procedure (transfer and/or ARMAX approach) and explain how you go about doing this. Perhaps there is a tutorial or an example available to do this in Stata?

Thanks!

Ward

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