Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Seperating COVID response from treatment effect #7

Open
mariano-recurve opened this issue Aug 14, 2020 · 3 comments
Open

Seperating COVID response from treatment effect #7

mariano-recurve opened this issue Aug 14, 2020 · 3 comments

Comments

@mariano-recurve
Copy link
Contributor

If you use impact due to COVID as a stratification parameter, and your treatment was active during the onset of COVID, how do you know you're getting COVID impact and not treatment impact during stratification?

Per Steve Schmidt's question

@steevschmidt
Copy link

Thanks for posting this Mariano. Clarifying my question/concern --

If treated customers are assigned to stratification bins based on "COVID-like" changes in energy use during the COVID period (e.g. "fractional change in usage"), and they were undergoing program treatment at the same time, it seems to me energy changes due to the program might cause them to be put in the wrong bin, and get an incorrect adjustment.

Using the effect of COVID to stratify program participants seems problematic, at least for residential behavioral programs where energy profile changes can vary widely both from the program treatment(s) and from COVID impacts.

To avoid this, bins could be created based only on pre-COVID characteristics.

@mcgeeyoung
Copy link
Contributor

That's right Steve. You couldn't use COVID as a parameter for a program that was in-flight at the onset of COVID.

@steevschmidt
Copy link

Got it, thanks for confirming.

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

3 participants