1. Bayesian hierarchical modeling of the temporal dynamics of subjective well-being: A 10 year longitudinal analysis
- Author
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Anglim, Jeromy, Weinberg, Melissa, and Cummins, Robert
- Subjects
PsyArXiv|Social and Behavioral Sciences| Social and Personality Psychology ,Social Psychology ,Lag ,Bayesian probability ,Probit ,Sample (statistics) ,Social and Behavioral Sciences ,FOS: Psychology ,PsyArXiv|Social and Behavioral Sciences ,Transformation (function) ,Quadratic equation ,Statistics ,Personality and Social Contexts ,bepress|Social and Behavioral Sciences ,Psychology ,Bayesian hierarchical modeling ,bepress|Social and Behavioral Sciences|Psychology|Personality and Social Contexts ,Subjective well-being ,PsyArXiv|Social and Behavioral Sciences|Social and Personality Psychology ,General Psychology - Abstract
This study demonstrates, for the first time, how Bayesian hierarchical modeling can be applied to yield novel insights into the long-term temporal dynamics of subjective well-being (SWB). Several models were proposed and examined using Bayesian methods. The models were assessed using a sample of Australian adults (n = 1081) who provided annual SWB scores on between 5 and 10 occasions. The best fitting models involved a probit transformation, allowed error variance to vary across participants, and did not include a lag parameter. Including a random linear and quadratic effect resulted in only a small improvement over the intercept only model. Examination of individual-level fits suggested that most participants were stable with a small subset exhibiting patterns of systematic change.
- Published
- 2015
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