Some thoughts on uniform prior probabilities when estimating P values and confidence intervals

[R_cubed]

@HuwLlewelyn

If I wish to estimate the posterior distribution of beta for the current study, then I do so by assuming a flat prior, b and SE1 = s/root(n1)

Why do you assume a flat prior after your first estimate? That amounts to ignoring the likelihood function from the first study.

Please study the following:

Kass, R. E. (1990). Data-translated likelihood and Jeffreys’s rules. Biometrika, 77(1), 107-114. (PDF)