# causal impact - adding multiple control groups

I want to run an analysis using causal impact tool. I have one test group but multiple control groups. Can I use multiple control groups all together in one model? Eg: Y = test and A,B,C as control all together as multivariate in this tool? Any suggestions?

Thanks

• What is the difference among your controls? How can they all be controls? – eric_kernfeld Feb 9 '16 at 6:17
• In causal statistics, causation is usually discussed relative to another potential situation. The effect of a drug is not well defined; one must estimate the effect of the drug relative to placebo or the effect of the drug relative to no treatment. Could you separately estimate effects relative to each of your control levels? – eric_kernfeld Feb 9 '16 at 6:19

Yes, absolutely. CausalImpact constructs a counterfactual to the observed post-intervention outcomes using a combination of all the control time series you enter. So in practice you almost always want at least a few control time series. Keep in mind that the model assumes all of these to be unaffected by the treatment.
plot(impact$model$bsts.model, "coefficients")