Figure 3.

Basis for Bayesian dynamic borrowing. a The “power prior” [61, 62, 66] is constructed from an uninformative prior, the likelihood of the external comparator data and a weighting parameter (“the power parameter”; depicted as ω) used to discount the external data, accounting for the either the measured or unmeasured differences in the populations. This power prior is then applied to the likelihood of the randomised controlled trial internal control data to estimate a Bayesian posterior distribution of the outcome. b Bayesian hierarchical models may assume that each source of data is sampled from a larger population [31, 70]. The resulting variability between sources is modelled as a random effect whose variance is to be estimated. Many sources of data are required to accurately model the variance without robust priors