Search

The probabilistic index (PI), also known as the probability of superiority or the common language effect size, refers to the probability that the outcome of a randomly selected subject exceeds the outcome of another randomly selected subject, conditional on the covariate values of both subjects. This summary measure has a long history, especially for the 2-sample design where the covariate value typically refers to 1 of 2 treatments. Despite some of the attractive features of the PI, it is often not used beyond the 2-sample design. One reason is the lack of a flexible regression framework that embeds the PI and that allows the user to estimate it for more complicated designs. However, Thas, De Neve, Clement, and Ottoy (2012) recently developed such a regression framework, named probabilistic index models (PIMs). In this tutorial we provide an introduction to PIMs where we discuss several theoretical properties, motivate why we think PIMs could be useful for behavioral sciences, and illustrate how it can be used in practice using the R package pim. [ABSTRACT FROM AUTHOR]

The Implicit Relational Assessment Procedure (IRAP) has been used to assess the probability of arbitrarily applicable relational responding or as an indirect measure of implicit attitudes. To date, IRAP effects have commonly been quantified using the D IRAP scoring algorithm, which was derived from Greenwald, Nosek and Banaji's (2003) D effect size measure. In the article, we highlight the difference between an effect size measure and a scoring algorithm, discuss the drawbacks associated with D , and propose an alternative: a probabilistic, semiparametric measure referred to as the Probabilistic Index (Thas, De Neve, Clement, & Ottoy, 2012). Using a relatively large IRAP dataset, we demonstrate how the PI is more robust to the influence of outliers and skew (which are typical of reaction time data). Finally, we conclude that PI models, in addition to producing point estimate scores, can also provide confidence intervals, significance tests, and afford the possibility to include covariates, all of which may aid single subject design studies. [ABSTRACT FROM AUTHOR]

Abstract: Purpose: This article explores resources that help formerly recruited young people in dealing with war-related adversity and subsequent challenges, hence fostering their resilience. Methods: Self-reports on pertinent resources were collected from 1,008 northern Ugandan youth, of whom 330 had formerly been recruited by the Lord's Resistance Army. Based on the conceptual framework developed by the Psychosocial Working Group, the reported resources were thematically clustered and quantitatively analyzed. Results: This study identified a range of human, social, and cultural resources, with little difference between groups. Religious beliefs, social support, and mental health resources were most frequently reported by former child soldiers. Conclusions: These results reveal a multitude of resources and suggest that it is important to build on these resources in interventions that aim to support former child soldiers in the aftermath of armed conflict. [Copyright &y& Elsevier]

Abstract: Purpose: Warfare takes a profound toll of all layers of society, creating multiple and multilevel challenges that impinge on the psychosocial well-being of affected individuals. This study aims to assess the scope and salience of challenges confronting former child soldiers and at identifying additional challenges they face compared to non-recruited young people in war-affected northern Uganda. Methods: The study was carried out with a stratified random sample of northern Ugandan adolescents (n = 1,008), of whom a third had formerly been recruited (n = 330). The mixed-method comparison design consisted of a constrained free listing task to determine the challenges; a free sorting task to categorize them into clusters; and statistical analysis of their prevalence among formerly recruited youth and of how they compare with those of nonrecruited youth. Results: Altogether, 237 challenges were identified and clustered into 15 categories, showing that formerly recruited participants mainly identified “emotional” and “training and skills”–related challenges. Compared with nonrecruited counterparts, they reported significantly more “emotional” and fewer “social and relational” challenges, with the exception of stigmatization. Overall, there was similarity between the challenges reported by both groups. Conclusions: The challenges confronting formerly recruited youths reach well beyond the effects of direct war exposure and emerge mainly from multiple influence spheres surrounding them. These challenges are largely shared in common with nonrecruited youths. This multidimensional and collective character of challenges calls for comprehensive psychosocial interventions through which healing the psychological wounds of war is complemented by mending the war-affected surroundings at all levels and in all life areas. [Copyright &y& Elsevier]