Date of Award
Master of Science in Statistics
Computer Science and Statistics
Statement of the problem: Recent years have demonstrated an increasing study of subjective happiness, often assessed by self-reported questionnaires (Gable & Haidt, 2005). The underlying physiological mechanisms of happiness are less well understood. This analysis examines scale reliability and validity in relation to biomarkers of stress responsiveness for scales of self-reported subjective well-being, to identify items that relate to an underlying physiology of happiness.
Methods: A principal components model is employed. Bayesian model estimation is used to address small sample size (N = 20). Additionally, sampling was clustered, including a subset of undergraduate students (n = 10) and a subset of graduate students (n = 10). To account for this structure to the data, group mean differences are estimated and compared. This improves model estimation and allows for a mean difference comparison which is insightful for possible sources of confounding. Three scales are included, measuring self-reported life events, life satisfaction, and happiness. Three biomarkers are included: cortisol (arousal signaler), interleukin-6 (inflammation cytokine), and global DNA methylation (regulator of protein expression including cortisol and interleukin-6).
Summary of results: All scales demonstrated internal structure validity and internal consistency reliability. Biomarkers demonstrated meaningful association with all scales, however in one case the direction of association was counter to expectations (life satisfaction positively associated with interleukin-6). Most group difference tests were nonsignificant, a lack of evidence of heterogeneity of measurement between groups. There were some scale items on that did demonstrate a significant difference.
Implications for scale use, and this procedure for measurement theory, are discussed.
Tanzer, Joshua Ray, "RELIABILITY AND PHYSIOLOGICAL VALIDITY: BAYESIAN PRINCIPAL COMPONENTS ANALYSIS AND GROUP COMPARISON" (2021). Open Access Master's Theses. Paper 1924.