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Multilevel modelling approach to analysing life course socioeconomic status and understanding missingness

Author

Listed:
  • Adrian Byrne

    (University of Nottingham)

  • Natalie Shlomo

    (University of Manchester)

  • Tarani Chandola

    (University of Hong Kong)

Abstract

This paper investigated the extent to which parental socioeconomic status was associated with life course socioeconomic status heterogeneity between adult cohort members of the 1958 National Child Development Study and how this association differed depending on methods used to address longitudinal missing data. We compared three variants of the full information maximum likelihood approach, namely available case, complete case and partially observed case and two methods designed to compensate for missing at random data, namely multilevel multiple imputation and multiple imputation chained equations. Our results highlighted the important contribution of parental socioeconomic status in explaining the divergence in achieved socioeconomic status over the adult life course, how the available case approach increasingly overestimated socioeconomic attainment as age increased and survey sample size decreased and how the complete case approach downwardly biased the effect of parental socioeconomic status on adult socioeconomic status.

Suggested Citation

  • Adrian Byrne & Natalie Shlomo & Tarani Chandola, 2023. "Multilevel modelling approach to analysing life course socioeconomic status and understanding missingness," Review of Evolutionary Political Economy, Springer, vol. 4(2), pages 275-297, July.
  • Handle: RePEc:spr:revepe:v:4:y:2023:i:2:d:10.1007_s43253-022-00081-8
    DOI: 10.1007/s43253-022-00081-8
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    References listed on IDEAS

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    1. Martin Nybom & Jan Stuhler, 2016. "Heterogeneous Income Profiles and Lifecycle Bias in Intergenerational Mobility Estimation," Journal of Human Resources, University of Wisconsin Press, vol. 51(1), pages 239-268.
    2. Yaojun Li & Fiona Devine, 2011. "Is Social Mobility Really Declining? Intergenerational Class Mobility in Britain in the 1990s and the 2000s," Sociological Research Online, , vol. 16(3), pages 28-41, August.
    3. Ganzeboom, H.B.G. & de Graaf, P.M. & Treiman, D.J. & de Leeuw, J., 1992. "A standard international socio-economic index of occupational status," WORC Paper 92.01.001/1, Tilburg University, Work and Organization Research Centre.
    4. Denise Hawkes & Ian Plewis, 2006. "Modelling non‐response in the National Child Development Study," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 169(3), pages 479-491, July.
    5. Bell, Andrew & Jones, Kelvyn, 2015. "Explaining Fixed Effects: Random Effects Modeling of Time-Series Cross-Sectional and Panel Data," Political Science Research and Methods, Cambridge University Press, vol. 3(1), pages 133-153, January.
    6. Andrew Bell & Malcolm Fairbrother & Kelvyn Jones, 2019. "Fixed and random effects models: making an informed choice," Quality & Quantity: International Journal of Methodology, Springer, vol. 53(2), pages 1051-1074, March.
    7. Steele, Fiona, 2008. "Multilevel models for longitudinal data," LSE Research Online Documents on Economics 52203, London School of Economics and Political Science, LSE Library.
    8. Harvey Goldstein & James R. Carpenter & William J. Browne, 2014. "Fitting multilevel multivariate models with missing data in responses and covariates that may include interactions and non-linear terms," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 177(2), pages 553-564, February.
    9. Stanislav Kolenikov & Gustavo Angeles, 2009. "Socioeconomic Status Measurement With Discrete Proxy Variables: Is Principal Component Analysis A Reliable Answer?," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 55(1), pages 128-165, March.
    10. Patrick Sturgis & Louise Sullivan, 2008. "Exploring social mobility with latent trajectory groups," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 171(1), pages 65-88, January.
    11. Erzsebet Bukodi & Shirley Dex & John Goldthorpe, 2011. "The conceptualisation and measurement of occupational hierarchies: a review, a proposal and some illustrative analyses," Quality & Quantity: International Journal of Methodology, Springer, vol. 45(3), pages 623-639, April.
    12. Fiona Steele, 2008. "Multilevel models for longitudinal data," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 171(1), pages 5-19, January.
    13. Martin Nybom & Jan Stuhler, 2017. "Biases in Standard Measures of Intergenerational Income Dependence," Journal of Human Resources, University of Wisconsin Press, vol. 52(3), pages 800-825.
    14. Asri Maharani & Gindo Tampubolon, 2014. "Unmet Needs for Cardiovascular Care in Indonesia," PLOS ONE, Public Library of Science, vol. 9(8), pages 1-10, August.
    15. Stephen Nickell, 1982. "The Determinants of Occupational Success in Britain," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 49(1), pages 43-53.
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