Bayesian inference for psychology,part IV: parameter estimation and Bayes factors

In the psychological literature, there are two seemingly different approaches to inference: that from estimation of posterior intervals and that from Bayes factors. We provide an overview of each method and show that a salient difference is the choice of models. The two approaches as commonly practiced can be unified with a certain model specification, now popular in the statistics literature, called spike-and-slab priors. A spike-and-slab prior is a mixture of a null model, the spike, with an effect model, the slab. The estimate of the effect size here is a function of the Bayes factor, showing that estimation and model comparison can be unified. The salient difference is that common Bayes factor approaches provide for privileged consideration of theoretically useful parameter values, such as the value corresponding to the null hypothesis, while estimation approaches do not. Both approaches, either privileging the null or not, are useful depending on the goals of the analyst.     

Therapeutic processes in group therapy: Intersections between general change mechanisms and motivational stages of change from patient perspective

Intersections between Grawe’s General Psychotherapy and Prochaska’s Transtheoretical Model were investigated in group therapy in a longitudinal design. It was assumed that general change mechanisms have an impact on patients’ stages of change. Specifically, the main hypotheses were that experiential change mechanisms (ECM; clarification of meaning, problem actuation, emotional bond and group cohesion) should be especially relevant for early stages of change (precontemplation and contemplation), whereas behavioral change mechanisms (BCM; resource activation, mastery/coping and task and goals) should be especially relevant for late stages of change (action and maintenance). Therefore, 140 outpatients attending different types of group therapy, with a typical duration of 8 sessions, were investigated. Patients completed the Form for the Evaluation of Therapeutic Processes in Group Therapy (FEPiG), the University of Rhode Island Change Assessment, short version (URICA-S) and several symptomatology measures (BDI-II, BSCL and IIP-32) at two measuring times. Intersections were analysed through correlational analyses, cross-lagged panels and a path-analytic model, supporting the hypotheses. Specifically, results suggested that experiencing ECM at t1 predicted higher levels of reported contemplation at t2. Patients experiencing higher levels of BCM at t1 reported higher levels of action at t2. Clinical implications of the results are discussed.     

The reliability and stability of visual working memory capacity

Because of the central role of working memory capacity in cognition, many studies have used short measures of working memory capacity to examine its relationship to other domains. Here, we measured the reliability and stability of visual working memory capacity, measured using a single-probe change detection task. In Experiment 1, the participants (N = 135) completed a large number of trials of a change detection task (540 in total, 180 each of set sizes 4, 6, and 8). With large numbers of both trials and participants, reliability estimates were high (α > .9). We then used an iterative down-sampling procedure to create a look-up table for expected reliability in experiments with small sample sizes. In Experiment 2, the participants (N = 79) completed 31 sessions of single-probe change detection. The first 30 sessions took place over 30 consecutive days, and the last session took place 30 days later. This unprecedented number of sessions allowed us to examine the effects of practice on stability and internal reliability. Even after much practice, individual differences were stable over time (average between-session r = .76).     

Perfectionism and coping with daily failures: positive reframing helps achieve satisfaction at the end of the day

Differentiating perfectionistic strivings and perfectionistic concerns, the present study examined how perfectionism predicts what coping strategies people use, when dealing with failures, and how perfectionism and coping influence people's satisfaction. A sample of 149 students completed daily reports for 3-14 days, reporting the most bothersome failure they experienced during the day, what strategies they used to cope with the failure, and how satisfied they felt at the end of the day. Multilevel regression analyses showed that perfectionistic concerns predicted more frequent use of self-blame, less frequent use of active coping and acceptance, and higher satisfaction at the end of the day, whereas perfectionistic strivings predicted less frequent use of self-blame and higher satisfaction. Although positive reframing, acceptance, and humor predicted higher satisfaction for all students, further analyses showed that positive reframing coping was particularly helpful for students high in perfectionistic concern. The findings suggest that accommodative coping strategies are generally helpful in dealing with personal failures, with positive reframing being a coping strategy that works particularly well for people high in perfectionistic concerns (who are prone to dissatisfaction) to achieve higher satisfaction at the end of the day.     

Could positive affect help engineer robot control systems?

Emotions have long been seen as counteracting rational thought, but over the last decades, they have been viewed as adaptive processes to optimize human (but also animal) behaviour. In particular, positive affect appears to be a functional aspect of emotions closely related to that. We argue that positive affect as understood in Kuhl’s PSI model of the human cognitive architecture appears to have an interpretation in state-of-the-art hybrid robot control architectures, which might help tackle some open questions in the field.     

Response specific temporal expectancy: Evidence from a variable foreperiod paradigm

When a stimulus-response event is frequently paired with a specific foreperiod, response performance for this event is improved after this foreperiod. This phenomenon is referred to as specific temporal expectancy. In four experiments, we investigated whether stimulus- or response-related processing benefits from specific temporal expectancy. In a speeded choice reaction task, different features of the imperative stimuli were frequently paired with foreperiods in such a way that only in some experiments were the responses also frequently paired with foreperiods. Participants revealed evidence for specific temporal expectancy when responses were frequently paired with foreperiods, but not when only the stimuli were frequently paired with foreperiods. We concluded that specific temporal expectancy affects response-related processing.     

Patterns, chunks, and hierarchies in serial reaction-time tasks

The impact of relational structures (i.e., the systematicity of relations between successive items) on incidental sequence learning was investigated in a serial reaction-time (SRT) task while keeping constant the statistical structure. In order to assess the influence of relational structures in stimulus and response sequences separately, the strength of relational patterns in sequences of digits as stimuli and of keystrokes as responses was orthogonally varied. In Exps. 1 and 2, the variation of relational patterns was mainly effective in the keystroke sequence. In Exp. 2, in addition to the variation of relational patterns, the presentation of stimuli was delayed at serial positions that were incongruent with the relational structure. The results show that these incongruent pauses reduced the learning of strongly structured sequences of keystrokes but improved the learning of weakly structured sequences. Experiment 3 suggests that even higher-order relations between elementary patterns are utilized to accelerate responses. The data are interpreted as evidence for the impact of relational patterns, in addition to statistical redundancies, on the formation of chunks. Reasons are discussed for the finding that relational chunking was more pronounced in the keystroke than in the digit sequences. Received: 25 June 1998 / Accepted: 3 December 1998