Confirmation by analogy

Abstract This paper proposes a framework for representing in Bayesian terms the idea that analogical arguments of various degrees strength may provide inductive support to yet untested scientific hypotheses. On this account, contextual information plays crucial role determining whether, and what extent, given similarity or dissimilarity between source target confirm an empirical hypothesis over rival one. In addition showing confirmation by analogy compatible with adoption standpoint, proposal outlined reveals close agreement fulfillment Hesse’s (Models analogies science, University Notre Dame Press, 1963) criteria capable attribution confirmatory power lights theory. sense, representation not only enriches framework, Hesse’s, enduring relevance understanding activity, but offer something akin proof concept it.