Linear models have been important statistical techniques fordealing with any experimental science. One important topic in this area is to detect influential subsets of data, that is, observations that are influential in terms of their effect on the estimation of parameters in linear regression or of the total population parameters.There are a lot of studies in radiocarbon dating to purpose a value consensus removing possible outliers after the corresponding testing. An influence analysis for the value consensus from a Bayesian perspective is developed in this paper.ABSTRACT SUBMITTED FOR POSTER SESSION