Informed Bayesian T-Tests

Across the empirical sciences, few statistical procedures rival the popularity of the frequentist t-test. In contrast, the Bayesian versions of the t-test have languished in obscurity. In recent years, however, the theoretical and practical advantages of the Bayesian t-test have become increasingly apparent and various Bayesian t-tests have been proposed, both objective ones (based on general desiderata) and subjective ones (based on expert knowledge). Here we propose a flexible t-prior for standardized effect size that allows computation of the Bayes factor by evaluating a single numerical integral. This specification contains previous objective and subjective t-test Bayes factors as special cases. Furthermore, we propose two measures for informed prior distributions that quantify the departure from the objective Bayes factor desiderata of predictive matching and information consistency. We illustrate the use of informed prior distributions based on an expert prior elicitation effort

bridgesampling: An R Package for Estimating Normalizing Constants

Statistical procedures such as Bayes factor model selection and Bayesian model averaging require the computation of normalizing constants (e.g., marginal likelihoods). These normalizing constants are notoriously difficult to obtain, as they usually involve high-dimensional integrals that cannot be solved analytically. Here we introduce an R package that uses bridge sampling (Meng & Wong, 1996; Meng & Schilling, 2002) to estimate normalizing constants in a generic and easy-to-use fashion. For models implemented in Stan, the estimation procedure is automatic. We illustrate the functionality of the package with three examples

Understanding the legitimation of the EU-Ukraine action plan–a discourse historical approach to EU foreign policy on Ukraine after the orange revolution

The recent expansion of the war in Ukraine calls for a better understanding of EU-Ukraine relations. This paper explicates the legitimation of EU foreign policy regarding Ukraine during and after the Orange Revolution. The aim of this paper is twofold. First, this research aims to uncover the intent behind the EU’s legitimation discourse vis-à-vis Ukraine following the Orange Revolution. An analysis of the EU’s legitimation discourse vis-à-vis Ukraine after the Orange Revolution fulfils the second aim of this paper: filling a gap in International Relations scholarship on EU-Ukraine relations. Following a formal- and content-related analysis of argumentation schemes, this paper argues that the EU perceived the Orange Revolution as an opportunity with which it could test its European Neighbourhood Policy in order to legitimise it taking action on the global stage. Since this paper helps to understand the legitimation of EU foreign policy towards Ukraine, it might provide a basis for the analysis of EU foreign policy regarding Ukraine in other timeframes and towards other states in the post-Soviet space.</p