Bringing causal models into the mainstream

May 10, 2011 § 1 Comment

Andrew Gelman points to John Johnson who has written a short piece about causal modeling in the mainstream. This blurb seems most important to me –

So, that leaves the last point, which may cause some controversy. “Do not try this at home.” Causal analysis does not have a SAS proc or simple R routine (perhaps with the exception of two-stage least squares). This is going to have to come at the end of perhaps hours of data exploration, modeling, testing, rejecting, trying something else, and finally accepting. A causal model is not always going to be easy to write into a statistical analysis plan, and primary investigators may not want something so fluid in the plan.

Although Johnson works primarily in the pharmaceutical industry where the processes of randomization and experiment design are quite rigorous, I think this point is quite important for the social sciences as well. Throughout this year I’ve found that causal analysis is too often the goal of observational studies, when in fact they should perhaps be a lot more careful in making any strong causal inferences from (what is likely to quite flawed) data. I have taken some extra pains to do this in my MA thesis, and I’m happier with it as a result.

Advertisements

§ One Response to Bringing causal models into the mainstream

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out / Change )

Twitter picture

You are commenting using your Twitter account. Log Out / Change )

Facebook photo

You are commenting using your Facebook account. Log Out / Change )

Google+ photo

You are commenting using your Google+ account. Log Out / Change )

Connecting to %s

What’s this?

You are currently reading Bringing causal models into the mainstream at Samarth Bhaskar.

meta

%d bloggers like this: