Bayesian hierarchical modeling of the temporal dynamics of subjective well-being: A 10 year longitudinal analysis
Data(s) |
01/12/2015
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Resumo |
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. |
Identificador | |
Idioma(s) |
eng |
Publicador |
Elsevier |
Relação |
http://dro.deakin.edu.au/eserv/DU:30078298/anglim-bayesianhier-inpress-2015.pdf http://dro.deakin.edu.au/eserv/DU:30078298/anglim-bayesianhierarchicalmodeling-2015.pdf http://www.dx.doi.org/10.1016/j.jrp.2015.08.003 |
Direitos |
2015, Elsevier |
Palavras-Chave | #Bayesian hierarchical models #Homeostasis #Longitudinal #Set-point theory #Subjective well-being |
Tipo |
Journal Article |