Improving measurement by accounting for time-varying fluctuations: design-based and model-based methods

Liang, Jinghui (2025) Improving measurement by accounting for time-varying fluctuations: design-based and model-based methods. PhD thesis, University of Glasgow.

Abstract

During an experimental or a survey session, participants adapt and change due to learning, fatigue, fluctuations in attention, or other physiological or environmental changes. This temporal variation affects measurement, potentially reducing research power and validity. This thesis discussed how time-varying fluctuations bias measurements and how dealing with these fluctuations can improve measurements in two typical psychological research environments: cognitive experiments and psychological measurements. Two methodological parts are presented. The first one reviews typical cognitive experimental designs, and provided methods to account for time-varying fluctuations and improve power in experimental studies. These methods are based on better randomization algorithm and advanced statistics models. The second part introduced how to control time-varying fluctuations in psychometric datasets by finite mixture models to increase validity. It also provides an online platform for better randomizing and counterbalancing surveys. Both parts found that dealing with time-varying fluctuations benefits to power and validity gains, therefore increasing the reproducibility of psychological studies.

• Item Type: Thesis (PhD)
• Qualification Level: Doctoral
• Additional Information: Supported by funding from the Chinese Scholarship Council (CSC no. 202108060121).
• Subjects: B Philosophy. Psychology. Religion > BF Psychology; R Medicine > RC Internal medicine > RC0321 Neuroscience. Biological psychiatry. Neuropsychiatry
• Colleges/Schools: College of Medical Veterinary and Life Sciences > School of Psychology & Neuroscience
• Funder's Name: Chinese Scholarship Council
• Supervisor's Name: Barr, Dr. Dale
• Date of Award: 2025
• Depositing User: Theses Team
• Unique ID: glathesis:2025-85576
• Copyright: Copyright of this thesis is held by the author.
• Date Deposited: 10 Nov 2025 10:54
• Last Modified: 10 Nov 2025 14:18
• Thesis DOI: 10.5525/gla.thesis.85576
• URI: https://theses.gla.ac.uk/id/eprint/85576

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