Evaluating manifest monotonicity using Bayes factors

The assumption of latent monotonicity in item response theory models for dichotomous data cannot be evaluated directly, but observable consequences such as manifest monotonicity facilitate the assessment of latent monotonicity in real data. Standard methods for evaluating manifest monotonicity typically produce a test statistic that is geared toward falsification, which can only provide indirect support in favor of manifest monotonicity. We propose the use of Bayes factors to quantify the degree of support available in the data in favor of manifest monotonicity or against manifest monotonicity. Through the use of informative hypotheses, this procedure can also be used to determine the support for manifest monotonicity over substantively or statistically relevant alternatives to manifest monotonicity, rendering the procedure highly flexible. The performance of the procedure is evaluated using a simulation study, and the application of the procedure is illustrated using empirical data. Keywords: Bayes factor, essential monotonicity, item response theory, latent monotonicity, manifest monotonicit

Increasing the statistical power of animal experiments with historical control data

Low statistical power reduces the reliability of animal research; yet, increasing sample sizes to increase statistical power is problematic for both ethical and practical reasons. We present an alternative solution using Bayesian priors based on historical control data, which capitalizes on the observation that control groups in general are expected to be similar to each other. In a simulation study, we show that including data from control groups of previous studies could halve the minimum sample size required to reach the canonical 80% power or increase power when using the same number of animals. We validated the approach on a dataset based on seven independent rodent studies on the cognitive effects of early-life adversity. We present an open-source tool, RePAIR, that can be widely used to apply this approach and increase statistical power, thereby improving the reliability of animal experiments

An n-of-one RCT for intravenous immunoglobulin G for inflammation in hereditary neuropathy with liability to pressure palsy (HNPP).

Paroxysmal Cerebral Disorder

Community singing, wellbeing and older people: implementing and evaluating an English singing tool for health intervention in Rome

Aim: The aim of this research was to explore the transferability and effectiveness of the English Silver Song Clubs model for older people in a different social and cultural context, i.e. in the capital city of Italy, Rome. Methods: A single condition, pre-test, post-test design was implemented. Participants completed two questionnaires: EQ-5D and York SF-12. Results: After the singing experience, participants showed a decrease in their levels of anxiety and depression. An improvement was also found from baseline to follow up in reported performance of usual activities. The English study showed a difference between the singing and non-singing groups at three and six months on mental health, and after three months on specific anxiety and depression measures. The current (Rome) study shows similar findings with an improvement on specific anxiety and depression items. Conclusions: Policy makers in different national contexts should consider social singing activities to promote the health and wellbeing of older adults as they are inexpensive to run and have been shown to be enjoyable and effective

A review of applications of the Bayes factor in psychological research

The last 25 years have shown a steady increase in attention for the Bayes factor as a tool for hypothesis evaluation and model selection. The present review highlights the potential of the Bayes factor in psychological research. We discuss six types of applications: Bayesian evaluation of point null, interval, and informative hypotheses, Bayesian evidence synthesis, Bayesian variable selection and model averaging, and Bayesian evaluation of cognitive models. We elaborate what each application entails, give illustrative examples, and provide an overview of key references and software with links to other applications. The paper is concluded with a discussion of the opportunities and pitfalls of Bayes factor applications and a sketch of corresponding future research lines

Editors' introduction: neoliberalism and/as terror

The articles in this special issue are drawn from papers presented at a conference entitled “Neoliberalism and/as Terror”, held at the Nottingham Conference Centre at Nottingham Trent University by the Critical Terrorism Studies BISA Working Group (CSTWG) on 15-16 September 2014. The conference was supported by both a BISA workshop grant and supplementary funds from Nottingham Trent University’s Politics and International Relations Department and the Critical Studies on Terrorism journal. Papers presented at the conference aimed to extend research into the diverse linkages between neoliberalism and terrorism, including but extending beyond the contextualisation of pre-emptive counterterrorism technologies and privatised securities within relevant economic and ideological contexts. Thus, the conference sought also to stimulate research into the ways that neoliberalism could itself be understood as terrorism, asking - amongst other questions - whether populations are themselves terrorised by neoliberal policy. The articles presented in this special issue reflect the conference aims in bringing together research on the neoliberalisation of counterterrorism and on the terror of neoliberalism