Statistical Modeling, Causal Inference, and Social Science

This is Jessica. AI-text detectors are coming to play a bigger role in adjudicating what texts are worthy of our attention. There was the surprising case of an apparently AI-generated short story winning the

I’ve often seen confusion between interactions in a regression model and correlations among the predictors. To keep it simple, consider the model y = b0 + b1*x1 + b2*x2 + b3*x1*x2 + error, and assume the predictors have been signed so that both b1 and b2 are positive. Then b3 represents the interaction. This has nothing to do with the joint distribution of x...

A couple of decades ago some political scientists at George Washington University started a blog, which they called the Monkey Cage. They invited me to contribute. This was back in 2008.

I haven’t thought about the Monkey Cage for awhile. At some point it became attached to the Washington Post, and they kept telling me that my posts were too bloggy and not journalistic...

Jessica writes:

I get so tired of people dumping on decision theory because real world decisions are complex. If decision theory is so deeply flawed, I’d love to know what alternative methods the critics advise for trying to evaluate and improve decision making in some real world setting. Should we give up on modeling completely because some cause problems for our assu...

Donna Spiegelman shares this presentation she gave at the recent American Causal Inference Conference. I like what she has to say.

Here are the two parts of the stable treatment value assumption: