Understanding the Differences Between Bayesian and Frequentist ...

Frequentist inference begins by assuming a null hypothesis to be true before data are collected (eg, that there is no effect of a particular treatment on survival). Investigators then collect data, analyze them, and ask, “How surprising is my result if there is actually no effect of the treatment on survival?” The data would be surprising if there ... See more

This probability of obtaining another data set as extreme as the one collected is known as the P value. The P value is often criticized for being misunderstood and misused in the field of medicine.2,3 For example, in contrast to popular belief, the P value is not a measure of how correct a hypothesis is, nor is it a measure of the size or importanc... See more

In this respect, Bayesian inference is more intuitive at its core and in closer alignment with our natural mode of probabilistic reasoning than frequentist inference. For example, we are more interested in the probability that 1 treatment is superior to another (Bayesian probability) than in the probability of obtaining certain data assuming the tr... See more