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Comparing Betas in Bayesian Linear Regression

If someone was interested in comparing betas across two separate models, is there any issue in using the following formula to determine that with Bayesian Linear Regression? Or is there perhaps a better way?

B=beta; se = standard error of beta.

z = (B1 - B2) / √(seB1^2 + seB2^2)


  • Hmmm. There are at least two solutions to this problem. The first is simple: just eyeball the posterior distributions of the beta's. Although informative, this is of course not a formal test. The second solution would be to compare the models with the beta's equal to the models with the beta's estimated freely. This would seem to require some new development though.


  • Thank you EJ.

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