Behavioral and neural markers of self-regulation

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Abstract/Contents

Abstract
The ability to manipulate behavior in service of long-term goals, self-regulation, has a long history of research and thought behind it. Yet despite its long history and the multitude of related concepts and measures self-regulation research suffers from a lack of transferable measures, models and interventions. One overlooked reason for this might be the focus on creating mechanistic stories while sacrificing measurement rigor. This dissertation explores the meaning of a 'marker' of self-regulation from a psychometric perspective. Our work highlights the importance of the required and varying statistical properties of a self-regulation marker depending on the research question. With respect to within-subjects analyses we present the largest comparison of behavioral self-regulation measures in their suitability for individual difference analyses using retest-reliability. Regarding between-subjects designs we show how extensive model comparisons can reveal conflicting narratives and how neural group differences might lie in properties other than the central tendency of distributions.

Description

Type of resource text
Form electronic resource; remote; computer; online resource
Extent 1 online resource.
Place California
Place [Stanford, California]
Publisher [Stanford University]
Copyright date 2019; ©2019
Publication date 2019; 2019
Issuance monographic
Language English

Creators/Contributors

Author Enkavi, Ayse Zeynep
Degree supervisor Poldrack, Russell A
Thesis advisor Poldrack, Russell A
Thesis advisor Knutson, Brian
Thesis advisor Wagner, Anthony David
Degree committee member Knutson, Brian
Degree committee member Wagner, Anthony David
Associated with Stanford University, Department of Psychology.

Subjects

Genre Theses
Genre Text

Bibliographic information

Statement of responsibility Ayse Zeynep Enkavi.
Note Submitted to the Department of Psychology.
Thesis Thesis Ph.D. Stanford University 2019.
Location electronic resource

Access conditions

Copyright
© 2019 by Ayse Zeynep Enkavi
License
This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).

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