Plausibility Functions and Exact Frequentist Inference

Plausibility functions and exact frequentist inference

Bayesian and Frequentist Inference for Ecological Inference

In this paper we propose Bayesian and frequentist approaches to ecological inference, based on R C contingency tables, including a covariate. The proposed Bayesian model extends the binomial-beta hierarchical model developed by King, Rosen and Tanner (1999) from the 2 2 case to the R C case. As in the 2 2 case, the inferential procedure employs Markov chain Monte Carlo (MCMC) methods. As such, ...

Bayesian Versus Frequentist Inference

1 Goals and Outline Throughout this book, the topic of order-restricted inference is dealt with almost exclusively from a Bayesian perspective. Some readers may wonder why the other main school for statistical inference – frequentist inference – has received so little attention here. Isn't it true that in the field of psychology, almost all inference is frequentist inference? The first goal of ...

Bayesian Frequentist Hybrid Inference

Bayesian and frequentist methods differ in many aspects, but share some basic optimality properties. In practice, there are situations in which one of the methods is more preferred by some criteria. We consider the case of inference about a set of multiple parameters, which can be divided into two disjoint subsets. On one set, a frequentist method may be favored and on the other, the Bayesian. ...

Statistical Inference Without Frequentist Justifications

Statistical inference is often justified by long-run properties of the sampling distributions, such as the repeated sampling rationale. These are frequentist justifications of statistical inference. I argue, in line with existing philosophical literature, but against a widespread image in empirical science, that these justifications are flawed. Then I propose a novel interpretation of probabili...