Bayesian hierarchical modeling of the temporal dynamics of subjective well-being: : A 10 year longitudinal analysis

• Autores: Jeromy Anglim, Melissa K. Weinberg, Robert A. Cummins
• Localización: Journal of Research in Personality, ISSN-e 1095-7251, Vol. 59, Nº. 1, 2015, págs. 1-14
• Idioma: inglés
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• Resumen

  • 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