Bayesian methods have inherent advantages in flexibility and uncertainty quantification, which is increasingly used in clinical research. Proper specification of prior distributions is essential to their valid application. This paper analyzes the properties and practical contexts of various priors, summarizes common selection issues, proposes a standardized specification process, and illustrates its application through simulations and case studies. To enhance research transparency and rigor, we propose standardized reporting of prior distributions.
