Detection of differential item functioning in Rasch models by boosting techniques

Methods for the identification of differential item functioning (DIF) in Rasch models are typically restricted to the case of two subgroups. A boosting algorithm is proposed that is able to handle the more general setting where DIF can be induced by several covariates at the same time. The covariates can be both continuous and (multi‐)categorical, and interactions between covariates can also be considered. The method works for a general parametric model for DIF in Rasch models. Since the boosting algorithm selects variables automatically, it is able to detect the items which induce DIF. It is demonstrated that boosting competes well with traditional methods in the case of subgroups. The method is illustrated by an extensive simulation study and an application to real data.     

Profiting from poverty

We consider whether and under what conditions it is morally illicit to profit from poverty. We argue that when profit counterfactually depends on poverty, the agent making the profit is morally obliged to relinquish it. Finally, we argue that the people to whom the profit should be redirected are those on whom it counterfactually depends.     

Conversation: The challenges of teaching in a “nano department”

A panel at the 2016 American Academy of Religion conference staged, taped, transcribed, and edited this conversation about the challenges and opportunities of teaching in a “nano department” – an undergraduate religion or religious studies department (or combined religion and philosophy department) with only one, two, or three faculty members. Two things quickly become evident: one is the impossibility of coverage of the full religious studies curriculum, and the other is the necessity for collaboration with other departments. Neither of these is unique to nano departments, but there exists an intimacy between students and faculty in small departments, a necessary freedom to rethink the place of the study of religion in the liberal arts curriculum, and a disruptive value in what can be critiqued and contributed from a marginalized position. Arguably, nano departments are the canaries in the academic coal mine, charting the future of the humanities that cannot be discerned from the vantage point of Research‐1 contexts.     

Overcoming procrastination: one-year follow-up and predictors of change in a randomized controlled trial of Internet-based cognitive behavior therapy

Procrastination is a common self-regulatory failure that can have a negative impact on well-being and performance. However, few clinical trials have been conducted, and no follow-up has ever been performed. The current study therefore aimed to provide evidence for the long-term benefits and investigate predictors of a positive treatment outcome among patients receiving Internet-based cognitive behavior therapy (ICBT). A total of 150 self-recruited participants were randomized to guided or unguided ICBT. Self-report measures of procrastination, depression, anxiety, and quality of life were distributed at pre-treatment assessment, post-treatment assessment, and one-year follow-up. Mixed effects models were used to investigate the long-term gains, and multiple linear regression for predictors of a positive treatment outcome, using the change score on the Irrational Procrastination Scale as the dependent variable. Intention-to-treat was implemented for all statistical analyses. Large within-group effect sizes for guided and unguided ICBT, Cohen’s d = .97–1.64, were found for self-report measures of procrastination, together with d = .56–.66 for depression and anxiety. Gains were maintained, and, in some cases, improved at follow-up. Guided and unguided ICBT did not differ from each other, mean differences ?.31–1.17, 95% CIs [?2.59–3.22], and none of the predictors were associated with a better result, bs ?1.45–1.61, 95% CIs [?3.14–4.26]. In sum, ICBT could be useful and beneficial in relation to managing procrastination, yielding great benefits up to one year after the treatment period has ended, with comparable results between guided and unguided ICBT.     

Creating state of the art,next-generation Virtual Reality exposure therapies for anxiety disorders using consumer hardware platforms: design considerations and future directions

Decades of research and more than 20 randomized controlled trials show that Virtual Reality exposure therapy (VRET) is effective in reducing fear and anxiety. Unfortunately, few providers or patients have had access to the costly and technical equipment previously required. Recent technological advances in the form of consumer Virtual Reality (VR) systems (e.g. Oculus Rift and Samsung Gear), however, now make widespread use of VRET in clinical settings and as self-help applications possible. In this literature review, we detail the current state of VR technology and discuss important therapeutic considerations in designing self-help and clinician-led VRETs, such as platform choice, exposure progression design, inhibitory learning strategies, stimuli tailoring, gamification, virtual social learning and more. We illustrate how these therapeutic components can be incorporated and utilized in VRET applications, taking full advantage of the unique capabilities of virtual environments, and showcase some of these features by describing the development of a consumer-ready, gamified self-help VRET application for low-cost commercially available VR hardware. We also raise and discuss challenges in the planning, development, evaluation, and dissemination of VRET applications, including the need for more high-quality research. We conclude by discussing how new technology (e.g. eye-tracking) can be incorporated into future VRETs and how widespread use of VRET self-help applications will enable collection of naturalistic “Big Data” that promises to inform learning theory and behavioral therapy in general.     

Probability,Approximate Truth,and Truthlikeness: More Ways out of the Preface Paradox

The so-called Preface Paradox seems to show that one can rationally believe two logically incompatible propositions. We address this puzzle, relying on the notions of truthlikeness and approximate truth as studied within the post-Popperian research programme on verisimilitude. In particular, we show that adequately combining probability, approximate truth, and truthlikeness leads to an explanation of how rational belief is possible in the face of the Preface Paradox. We argue that our account is superior to other solutions of the paradox, including a recent one advanced by Hannes Leitgeb (Analysis 74.1).     

Answer Sets and Qualitative Decision Making

Logic programs under answer set semantics have become popular as a knowledge representation formalism in Artificial Intelligence. In this paper we investigate the possibility of using answer sets for qualitative decision making. Our approach is based on an extension of the formalism, called logic programs with ordered disjunction (LPODs). These programs contain a new connective called ordered disjunction. The new connective allows us to represent alternative, ranked options for problem solutions in the heads of rules: A × B intuitively means: if possible A, but if A is not possible then at least B. The semantics of logic programs with ordered disjunction is based on a preference relation on answer sets. We show that LPODs can serve as a basis for qualitative decision making.