Hierarchical Approximate Bayesian Computation

Approximate Bayesian computation (ABC) is a powerful technique for estimating the posterior distribution of a model’s parameters. It is especially important when the model to be fit has no explicit likelihood function, which happens for computational (or simulation-based) models such as those that are popular in cognitive neuroscience and other areas in psychology. However, ABC is usually applied only to models with few parameters. Extending ABC to hierarchical models has been difficult because high-dimensional hierarchical models add computational complexity that conventional ABC cannot accommodate. In this paper, we summarize some current approaches for performing hierarchical ABC and introduce a new algorithm called Gibbs ABC. This new algorithm incorporates well-known Bayesian techniques to improve the accuracy and efficiency of the ABC approach for estimation of hierarchical models. We then use the Gibbs ABC algorithm to estimate the parameters of two models of signal detection, one with and one without a tractable likelihood function.     

Is the Male Advantage in Mental-Rotation Performance Task Independent? On the Usability of Chronometric Tests and Paper-and-Pencil Tests in Children

This article presents a reanalysis of the data of 862 second and fourth graders collected in two previous studies, focusing on the influence of method (psychometric vs. chronometric) and stimulus type on the gender difference in mental-rotation accuracy. The children had to solve mental-rotation tasks with animal pictures, letters, or cube figures, either in a chronometric condition (computerized) or in a psychometric condition (paper-and-pencil). Results show a slight male advantage in mental-rotation accuracy, which is neither influenced by method nor by stimulus type. However, mental-rotation accuracy differed between the stimulus types, with the highest accuracy in animal pictures and the lowest accuracy in cube figures, and between age groups, with better performance in fourth graders than in second graders in both conditions. Results show that psychometric and chronometric mental-rotation tests with all the stimulus types are more or less similarly usable with children of that age.     

The Effects of Social and Physical Functioning and Self-Management Abilities on Well-Being Among Patients with Cardiovascular Diseases,Chronic Obstructive Pulmonary Disease,and Diabetes

To increase our understanding of relationships between well-being and social/physical functioning and self-management abilities (SMAs) among chronically ill patients. The cross-sectional questionnaire-based study included 1,254 patients with cardiovascular diseases, 725 with chronic obstructive pulmonary disease, and 253 with diabetes (total, 2232/4200; 53 % response rate). Social and physical functioning correlated significantly with SMAs and well-being (all p?≤?0.001). After controlling for background characteristics, multiple regression showed that social and physical functioning were still related to SMAs (β?=?0.32–0.12; both p?≤?0.001) and well-being (β?=?0.39–0.14; both p?≤?0.001). The strengths of relationships between well-being and social (β?=?0.39 vs. 0.20) and physical (β?=?0.14 vs. 0.07) functioning declined significantly (both p?≤?0.001) when the SMA mediator was included in the equation. SMAs of chronically ill are related to their social and physical functioning. We found indications that chronically ill patients reporting lower levels of social and physical functioning are worse self-managers than are those with higher levels of functioning. Furthermore, SMAs may mediate the relationships between social and physical functioning and well-being. Self-management interventions aiming to enhance SMAs more broadly than traditional interventions aiming only to prevent functional decline are expected to improve SMAs and enhance well-being among chronically ill patients.