In Reply to Chowdhry et al.

We thank the authors for their response 1 Chowdhry AK Mayo D Pugh SL Park J Fuller CD Kang J. In regard to Fornacon-Wood et al. [Letter to the Editor]. Int J Radiat Oncol Biol Phys. 2022; Google Scholar to our “statistics for the people” article 2 Fornacon-Wood I Mistry H Johnson-Hart C Faivre-Finn C O'Connor JPB Price GJ Understanding the differences between Bayesian and frequentist statistics. Int J Radiat Oncol Biol Phys. 2022; 112: 1076-1082 Abstract Full Text Full Text PDF PubMed Scopus (2) Google Scholar that aimed to introduce perhaps unfamiliar readers to Bayesian statistics and some potential advantages of their use. We agree that frequentist statistics are a useful and widespread statistical analytical approach, and we are not aiming to revisit the frequentist versus Bayesian arguments that have been well articulated in the literature. 3 Dienes Z. Bayesian versus orthodox statistics: Which side are you on?. Perspect Psychol Sci. 2011; 6: 274-290 Crossref PubMed Scopus (640) Google Scholar , 4 Harrell FE. My journey from frequentist to Bayesian statistics. Available at: https://www.fharrell.com/post/journey/. Accessed July 25, 2022. Google Scholar , 5 Zampieri FG Casey JD Shankar-Hari M Harrell FE Harhay MO. Using Bayesian methods to augment the interpretation of critical care trials. An overview of theory and example reanalysis of the alveolar recruitment for acute respiratory distress syndrome trial. Am J Respir Crit Care Med. 2021; 203: 543-552 Crossref PubMed Scopus (29) Google Scholar However, there are a couple of points we would like to make.