Abstract
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.
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References
Asparouhov T.: Sampling weights in latent variable modeling. Struct. Equ. Model. 12(3), 411–434 (2005)
Bollen K.A., Curran P.J.: Latent Curve Models. A Structural Equation Perspective. Wiley, Hoboken (2006)
Collins, L.M., Sayer, A.G. (eds): New Methods for the Analysis of Change. American Psychological Association, Washington (2001)
Chambers, R.L., Skinner, C.J. (eds): Analysis of Survey Data. Wiley, Chichester (2003)
Christoph B., Noll H.H.: Subjective well-being in the European Union during the 90s. Soc. Indic. Res. 64, 521–546 (2003)
Dancan G.: Using panel studies to understand household behaviour and well-being. In: Rose, D. (eds) Researching Social and Economic Change: The Uses of Household Panel Studies, Routledge, London (2000)
Dolan P., Peasgood T.: Measuring well-being for public policy: preferences or experiences?. J. Leg. Stud. 37, 5–31 (2008)
Dolan P., Peasgood T., White M.: Do we really know what makes us happy? A review of the economic literature on the factors associated with subjective well-being. J. Econ. Psychol. 29, 94–122 (2008)
Duncan T., Duncan S., Strycker L.: An Introduction to Latent Variable Growth Curve Modeling. Concepts, Issues, and Applications. Lawrence Erlbaum Associates, Mahwah (2006)
Hancock G.R., Kuo W.-L., Lawrence F.R.: An illustration of second-order latent growth models. Struct. Equ. Model. 8(3), 470–489 (2001)
Helliwell J.F.: How’s life? Combining individual and national variables to explain subjective well-being. Econ. Model. 20, 331–360 (2003)
Judge T.A., Watanabe S.: Another look at the job satisfaction-life satisfaction relationship. J. Appl. Psychol. 78(6), 939–948 (1993)
Khattab N., Fenton S.: What makes young adults happy? Employment and non-work as determinants of life satisfaction. Sociology 43(1), 11–26 (2009)
Lucas R.E., Donnellan M.B.: How stable is happiness? Using the STARTS model to estimate the stability of life satisfaction. J. Res. Pers. 41, 1091–1098 (2007)
McArdle, J.J. : Dynamic but structural equation modeling of repeated measures. In: Nesselroade, J.R., Cattell, R.B. (eds.) TheHandbook of Multivariate Experimental Psychology, pp. 561–614. Plenum Press, New York (1988)
Meredith W., Tisak J.: Latent curve analysis. Psychometrika 55(1), 107–122 (1990)
Muthén, B.O.: Mplus Technical Appendices. Vol. 2, Muthén & Muthén, Los Angeles (1998–2004)
Muthén, L.K., Muthén, B.O. : Mplus User’s Guide. Vol. 5, Muthén & Muthén, Los Angeles (1998–2007)
Muthén, B.O., du Toit, S.H.C., Spisic, D.: Robust inference using weighted least squares and quadratic estimating equations in latent variable modeling with categorical and continuous outcomes. Unpublished manuscript. University of California, Los Angeles (1997)
Preacher K.J., Wichman A.L., MacCallum R.C., Briggs N.E.: Latent Growth Curve Modeling. Sage publications, Thousand Oaks (2008)
Skinner C.J., Vieira M.D.T.: Variance estimation in the analysis of clustered longitudinal survey data. Surv. Methodol. 33(1), 3–12 (2007)
Skinner, C.J., Holt, D., Smith, T.M.F. (eds): Analysis of Complex Surveys. Wiley, Chichester (1989)
Taylor, M.F., Brice, J., Buck, N., Prentice-Lane, E. (eds.): British Household Panel Survey User Manual Volume A: Introduction, Technical Report and Appendices. University of Essex, Colchester (2008)
Vieira M.D.T., Skinner C.J.: Estimating models for panel survey data under complex sampling. J. Off. Stat. 24, 343–364 (2008)
Vieira J.C., Menezes A., Gabriel P.: Low pay, higher pay and job quality: empirical evidence for Portugal. Appl. Econ. Lett. 12, 505–511 (2005)
White H.: A heteroscedasticity-consistent covariance matrix estimator and a direct test for heteroscedasticity. Econometrica 48(4), 817–838 (1980)
Yang C.-C., Yang C.-C., Yeh K.-H.: Ecological-inference-based latent growth models: modeling changes of alienation. Qual. Quant. 39, 125–135 (2005)
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Salgueiro, M.F., Smith, P.W.F. & Vieira, M.D.T. A multi-process second-order latent growth curve model for subjective well-being. Qual Quant 47, 735–752 (2013). https://doi.org/10.1007/s11135-011-9541-y
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DOI: https://doi.org/10.1007/s11135-011-9541-y