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Sample composition and representativeness on Understanding Society

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  • Peter Lynn
  • Pablo Cabrera‐Álvarez
  • Paul Clarke

Abstract

In this paper, we provide an overview of the sample design of Understanding Society and the consequent nature of design weights as well as a description of procedures that are implemented in order to maximise participation by sample members and procedures that are implemented to produce non‐response adjustments to the design weights. We then present some indicators of sample representativeness at the initial wave and of the impact that subsequent sample attrition has on this before concluding with some reflections on the nature of representativeness and estimation methods in the context of a highly complex sample design and complex patterns of missing data arising from non‐response.

Suggested Citation

  • Peter Lynn & Pablo Cabrera‐Álvarez & Paul Clarke, 2023. "Sample composition and representativeness on Understanding Society," Fiscal Studies, John Wiley & Sons, vol. 44(4), pages 341-359, December.
    • Handle: RePEc:wly:fistud:v:44:y:2023:i:4:p:341-359
    DOI: 10.1111/1475-5890.12357
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    References listed on IDEAS

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    1. Laura Fumagalli & Heather Laurie & Peter Lynn, 2013. "Experiments with methods to reduce attrition in longitudinal surveys," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 176(2), pages 499-519, February.
    2. Bianchi Annamaria & Biffignandi Silvia & Lynn Peter, 2017. "Web-Face-to-Face Mixed-Mode Design in a Longitudinal Survey: Effects on Participation Rates, Sample Composition, and Costs," Journal of Official Statistics, Sciendo, vol. 33(2), pages 385-408, June.
    3. D. Pfeffermann & C. J. Skinner & D. J. Holmes & H. Goldstein & J. Rasbash, 1998. "Weighting for unequal selection probabilities in multilevel models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 60(1), pages 23-40.
    4. Shaun R. Seaman & Ian R. White & Andrew J. Copas & Leah Li, 2012. "Combining Multiple Imputation and Inverse-Probability Weighting," Biometrics, The International Biometric Society, vol. 68(1), pages 129-137, March.
    5. Kaminska Olena & Lynn Peter, 2017. "The Implications of Alternative Allocation Criteria in Adaptive Design for Panel Surveys," Journal of Official Statistics, Sciendo, vol. 33(3), pages 781-799, September.
    6. Wooldridge, Jeffrey M., 2007. "Inverse probability weighted estimation for general missing data problems," Journal of Econometrics, Elsevier, vol. 141(2), pages 1281-1301, December.
    7. Lynn Peter & Kaminska Olena & Goldstein Harvey, 2014. "Panel Attrition: How Important is Interviewer Continuity?," Journal of Official Statistics, Sciendo, vol. 30(3), pages 1-15, September.
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    Cited by:

    1. Michaela Benzeval & Edith Aguirre & Meena Kumari, 2023. "Understanding Society: health, biomarker and genetic data," Fiscal Studies, John Wiley & Sons, vol. 44(4), pages 399-415, December.
    2. Michaela Benzeval & Thomas F. Crossley & Edith Aguirre, 2023. "A symposium on Understanding Society, the UK Household Longitudinal Study: introduction," Fiscal Studies, John Wiley & Sons, vol. 44(4), pages 317-340, December.
    3. Paul Fisher & Omar Hussein, 2023. "Understanding Society: the income data," Fiscal Studies, John Wiley & Sons, vol. 44(4), pages 377-397, December.

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