Dynamic Structural Equations in Discrete and Continuous Time

Author(s):  
Hermann Singer
2021 ◽  
Vol 15 ◽  
Author(s):  
Antti Veikko Petteri Veilahti ◽  
Levas Kovarskis ◽  
Benjamin Ultan Cowley

Neurofeedback for attention deficit/hyperactivity disorder (ADHD) has long been studied as an alternative to medication, promising non-invasive treatment with minimal side-effects and sustained outcome. However, debate continues over the efficacy of neurofeedback, partly because existing evidence for efficacy is mixed and often non-specific, with unclear relationships between prognostic variables, patient performance when learning to self-regulate, and treatment outcomes. We report an extensive analysis on the understudied area of neurofeedback learning. Our data comes from a randomised controlled clinical trial in adults with ADHD (registered trial ISRCTN13915109; N = 23; 13:10 female:male; age 25–57). Patients were treated with either theta-beta ratio or sensorimotor-rhythm regimes for 40 one-hour sessions. We classify 11 learners vs 12 non-learners by the significance of random slopes in a linear mixed growth-curve model. We then analyse the predictors, outcomes, and processes of learners vs non-learners, using these groups as mutual controls. Significant predictive relationships were found in anxiety disorder (GAD), dissociative experience (DES), and behavioural inhibition (BIS) scores obtained during screening. Low DES, but high GAD and BIS, predicted positive learning. Patterns of behavioural outcomes from Test Of Variables of Attention, and symptoms from adult ADHD Self-Report Scale, suggested that learning itself is not required for positive outcomes. Finally, the learning process was analysed using structural-equations modelling with continuous-time data, estimating the short-term and sustained impact of each session on learning. A key finding is that our results support the conceptualisation of neurofeedback learning as skill acquisition, and not merely operant conditioning as originally proposed in the literature.


2007 ◽  
Vol 44 (02) ◽  
pp. 285-294 ◽  
Author(s):  
Qihe Tang

We study the tail behavior of discounted aggregate claims in a continuous-time renewal model. For the case of Pareto-type claims, we establish a tail asymptotic formula, which holds uniformly in time.


2015 ◽  
Vol 14 (2) ◽  
pp. 70-79 ◽  
Author(s):  
Simon L. Albrecht

The job demands-resources (JD-R) model provides a well-validated account of how job resources and job demands influence work engagement, burnout, and their constituent dimensions. The present study aimed to extend previous research by including challenge demands not widely examined in the context of the JD-R. Furthermore, and extending self-determination theory, the research also aimed to investigate the potential mediating effects that employees’ need satisfaction as regards their need for autonomy, need for belongingness, need for competence, and need for achievement, as components of a higher order needs construct, may have on the relationships between job demands and engagement. Structural equations modeling across two independent samples generally supported the proposed relationships. Further research opportunities, practical implications, and study limitations are discussed.


2003 ◽  
Vol 48 (5) ◽  
pp. 680-683 ◽  
Author(s):  
Alexander von Eye

2018 ◽  
Vol 23 (4) ◽  
pp. 774-799 ◽  
Author(s):  
Charles C. Driver ◽  
Manuel C. Voelkle

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