Shaping of three-man teams on a multiple DRL-DRH schedule using collective reinforcement

Five three-man teams were conditioned to a multiple DRL-DRH schedule during five daily sessions of 3 hr each. The teams were conditioned on the basis of their cumulative response rate regardless of the contributions of individual members. Two individually conditioned Ss were run under a similar schedule for comparison. Although all teams demonstrated some differentiation of response rate under the two legs of the schedule, this difference was not achieved as rapidly, nor was it as stable, as the differentiation in rates achieved in individually conditioned Ss. Team members displayed a variety of response rates as a result of collective team conditioning. Often, individual response rates interfered with obtainment of team reinforcement. The individual team members displayed little S^D control in comparison with the individually conditioned Ss. In general the results suggest that collective reinforcement is highly inefficient in comparison with procedures employing individual feedback.     

Bayesian inference for psychology. Part II: Example applications with JASP

Bayesian hypothesis testing presents an attractive alternative to p value hypothesis testing. Part I of this series outlined several advantages of Bayesian hypothesis testing, including the ability to quantify evidence and the ability to monitor and update this evidence as data come in, without the need to know the intention with which the data were collected. Despite these and other practical advantages, Bayesian hypothesis tests are still reported relatively rarely. An important impediment to the widespread adoption of Bayesian tests is arguably the lack of user-friendly software for the run-of-the-mill statistical problems that confront psychologists for the analysis of almost every experiment: the t-test, ANOVA, correlation, regression, and contingency tables. In Part II of this series we introduce JASP (http://www.jasp-stats.org), an open-source, cross-platform, user-friendly graphical software package that allows users to carry out Bayesian hypothesis tests for standard statistical problems. JASP is based in part on the Bayesian analyses implemented in Morey and Rouder’s BayesFactor package for R. Armed with JASP, the practical advantages of Bayesian hypothesis testing are only a mouse click away.     

Bayesian inference for psychology. Part I: Theoretical advantages and practical ramifications

Bayesian parameter estimation and Bayesian hypothesis testing present attractive alternatives to classical inference using confidence intervals and p values. In part I of this series we outline ten prominent advantages of the Bayesian approach. Many of these advantages translate to concrete opportunities for pragmatic researchers. For instance, Bayesian hypothesis testing allows researchers to quantify evidence and monitor its progression as data come in, without needing to know the intention with which the data were collected. We end by countering several objections to Bayesian hypothesis testing. Part II of this series discusses JASP, a free and open source software program that makes it easy to conduct Bayesian estimation and testing for a range of popular statistical scenarios (Wagenmakers et al. this issue).     

Einige Versuche zur Frage der harmonischen Zusammenstellung gefärbter Flächenstücke

Zusammenfassung Es werden einige Versuche mitgeteilt, die anzeigen, daß Farbenharmonien dann auftreten, wenn die Größen der gefärbten Flächenstücke so gewählt werden, daß die sog. Helligkeitsäquivalente im Verhältnis 11 stehen.     

Understanding community re-entry of former prisoners with mental illness: a conceptual model to guide new research

Criminal justice, mental health, and social service professionals face a myriad of role expectations in working with prisoners with mental illness to facilitate community re-entry. These expectations include those related to law enforcement, social welfare, and administrative efficiency. The challenge for front line workers and the multiple systems that employ them is to integrate all these expectations effectively on behalf of the individual as well as the community. Current models of re-entry for individuals leaving prison with mental illness focus on the management and interaction of service systems. This paper presents a model of prisoner re-entry that incorporates a larger social context, illustrating dynamics related to both individuals with mental illness leaving prison and their interaction with the community setting. This model was generated through an interdisciplinary team effort. It was refined through a focus group process that included advocates, community members and other informants from mental health and criminal justice systems in five states. The model is designed to generate new questions for research that address both individual and community level issues.