Skip to main content

Advertisement

Log in

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

  • Published:
Quality & Quantity Aims and scope Submit manuscript

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.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • Asparouhov T.: Sampling weights in latent variable modeling. Struct. Equ. Model. 12(3), 411–434 (2005)

    Article  Google Scholar 

  • Bollen K.A., Curran P.J.: Latent Curve Models. A Structural Equation Perspective. Wiley, Hoboken (2006)

    Google Scholar 

  • Collins, L.M., Sayer, A.G. (eds): New Methods for the Analysis of Change. American Psychological Association, Washington (2001)

    Google Scholar 

  • Chambers, R.L., Skinner, C.J. (eds): Analysis of Survey Data. Wiley, Chichester (2003)

    Google Scholar 

  • Christoph B., Noll H.H.: Subjective well-being in the European Union during the 90s. Soc. Indic. Res. 64, 521–546 (2003)

    Article  Google Scholar 

  • 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)

    Google Scholar 

  • Dolan P., Peasgood T.: Measuring well-being for public policy: preferences or experiences?. J. Leg. Stud. 37, 5–31 (2008)

    Article  Google Scholar 

  • 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)

    Article  Google Scholar 

  • Duncan T., Duncan S., Strycker L.: An Introduction to Latent Variable Growth Curve Modeling. Concepts, Issues, and Applications. Lawrence Erlbaum Associates, Mahwah (2006)

    Google Scholar 

  • 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)

    Article  Google Scholar 

  • Helliwell J.F.: How’s life? Combining individual and national variables to explain subjective well-being. Econ. Model. 20, 331–360 (2003)

    Article  Google Scholar 

  • Judge T.A., Watanabe S.: Another look at the job satisfaction-life satisfaction relationship. J. Appl. Psychol. 78(6), 939–948 (1993)

    Article  Google Scholar 

  • Khattab N., Fenton S.: What makes young adults happy? Employment and non-work as determinants of life satisfaction. Sociology 43(1), 11–26 (2009)

    Article  Google Scholar 

  • 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)

    Article  Google Scholar 

  • 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)

    Chapter  Google Scholar 

  • Meredith W., Tisak J.: Latent curve analysis. Psychometrika 55(1), 107–122 (1990)

    Article  Google Scholar 

  • Muthén, B.O.: Mplus Technical Appendices. Vol. 2, Muthén & Muthén, Los Angeles (1998–2004)

    Google Scholar 

  • Muthén, L.K., Muthén, B.O. : Mplus User’s Guide. Vol. 5, Muthén & Muthén, Los Angeles (1998–2007)

    Google Scholar 

  • 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)

    Google Scholar 

  • Skinner C.J., Vieira M.D.T.: Variance estimation in the analysis of clustered longitudinal survey data. Surv. Methodol. 33(1), 3–12 (2007)

    Google Scholar 

  • Skinner, C.J., Holt, D., Smith, T.M.F. (eds): Analysis of Complex Surveys. Wiley, Chichester (1989)

    Google Scholar 

  • 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)

    Google Scholar 

  • Vieira M.D.T., Skinner C.J.: Estimating models for panel survey data under complex sampling. J. Off. Stat. 24, 343–364 (2008)

    Google Scholar 

  • 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)

    Article  Google Scholar 

  • White H.: A heteroscedasticity-consistent covariance matrix estimator and a direct test for heteroscedasticity. Econometrica 48(4), 817–838 (1980)

    Article  Google Scholar 

  • 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)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to M. Fátima Salgueiro.

Rights and permissions

Reprints and permissions

About this article

Cite this article

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

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11135-011-9541-y

Keywords

Navigation