A multi-process second-order latent growth curve model for subjective well-being

• Autor(a) principal: Salgueiro, M. F.
• Data de Publicação: 2013
• Outros Autores: Smith, P. W. F., Vieira, M. D. T.
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: https://ciencia.iscte-iul.pt/public/pub/id/310; http://hdl.handle.net/10071/9810
• topic: BHPS; Complex survey design; Latent growth curve model; Multi-process model; Subjective well-being

This article proposes a new approach to modelling longitudinal perceptions of subjective well-being (SWB). Several measures have been proposed in the literature to assess SWB and its determinants. Statistical approaches adopted include ordered probit models, fixed and random effects models and cross-lagged structural equation models. The British Household Panel Survey (BHPS) is a longitudinal national representative survey and contains several measures of SWB. Using BHPS data from 2002 to 2005, this article considers two main latent dimensions of life satisfaction: satisfaction with leisure and satisfaction with material issues. The latent trajectories of these two latent life satisfaction dimensions are simultaneously modeled in Mplus, using a multi-process, second-order latent growth curve model. Significant determinants of leisure and material satisfaction growth trajectories include socio-demographic characteristics, number of children in the household, number of hours worked per week, income and perceived health status.