Thanks to Kit Baum, a revised version of itsa is now available on SSC. itsa performs interrupted time series analysis for single and multiple groups
itsa estimates the effect of an intervention when the outcome variable is ordered as a time series, and a number of observations are available in both pre- and post-intervention periods. The study design is generally referred to as an interrupted time series because the intervention is expected to "interrupt" the level and/or trend subsequent to its introduction. itsa is a wrapper program for, by default, newey, which produces Newey-West standard errors for coefficients estimated by OLS regression, or optionally prais, which uses the generalized least-squares method to estimate the parameters in a linear regression model in which the errors are assumed to follow a first-order autoregressive process. itsa estimates treatment effects for either a single treatment group (with pre- and post-intervention observations) or a multiple-group comparison (i.e., the single treatment group is compared with one or more control groups). Additionally, itsa can estimate treatment effects for multiple treatment periods.
This revision includes two major changes. First, the user can now specify the option posttrend and the program will automatically provide post-estimation tables of the post-intervention trends for the treatment groups under study as well as their contrasts. The second major change is that in the figures produced by itsa (when specified as an option), all linear estimates will appear as segments that end at the vertical line representing the intervention period(s). Additionally, model specification information is placed in a note on the figure, so that the figure is now more self-explanatory.
I would like to acknowledge Steve Samuels for his assistance with these two major changes. He did a great job!
Finally, for interested parties, a paper describing the itsa command is forthcoming in the Stata Journal.
Ariel
itsa estimates the effect of an intervention when the outcome variable is ordered as a time series, and a number of observations are available in both pre- and post-intervention periods. The study design is generally referred to as an interrupted time series because the intervention is expected to "interrupt" the level and/or trend subsequent to its introduction. itsa is a wrapper program for, by default, newey, which produces Newey-West standard errors for coefficients estimated by OLS regression, or optionally prais, which uses the generalized least-squares method to estimate the parameters in a linear regression model in which the errors are assumed to follow a first-order autoregressive process. itsa estimates treatment effects for either a single treatment group (with pre- and post-intervention observations) or a multiple-group comparison (i.e., the single treatment group is compared with one or more control groups). Additionally, itsa can estimate treatment effects for multiple treatment periods.
This revision includes two major changes. First, the user can now specify the option posttrend and the program will automatically provide post-estimation tables of the post-intervention trends for the treatment groups under study as well as their contrasts. The second major change is that in the figures produced by itsa (when specified as an option), all linear estimates will appear as segments that end at the vertical line representing the intervention period(s). Additionally, model specification information is placed in a note on the figure, so that the figure is now more self-explanatory.
I would like to acknowledge Steve Samuels for his assistance with these two major changes. He did a great job!
Finally, for interested parties, a paper describing the itsa command is forthcoming in the Stata Journal.
Ariel
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