Scientists have found a way to improve the accuracy of comparing two lognormal populations by using special priors. These priors help solve the problem of arbitrary constants in Bayesian hypothesis testing. The new method gives more reliable results when testing if two lognormal means are equal, as shown in real and simulated data.