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Nonresponse bias adjustments: what can process data contribute?

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  • G. Blom, Annelies

Abstract

To minimise nonresponse bias most large-scale social surveys undertake nonresponse weighting. Traditional nonresponse weights adjust for demographic information only. This paper assesses the effect and added value of weights based on fieldwork process data in the European Social Survey (ESS). The reduction of relative nonresponse bias in estimates of political activism, trust, happiness and human values was examined. The effects of process, frame and post-stratification weights, as well as of weights combining several data sources, were examined. The findings demonstrate that process weights add explanatory power to nonresponse bias adjustments. Combined demographic and process weights were most successful at removing nonresponse bias.

Suggested Citation

  • G. Blom, Annelies, 2009. "Nonresponse bias adjustments: what can process data contribute?," ISER Working Paper Series 2009-21, Institute for Social and Economic Research.
    • Handle: RePEc:ese:iserwp:2009-21
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    File URL: https://www.iser.essex.ac.uk/wp-content/uploads/files/working-papers/iser/2009-21.pdf
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    References listed on IDEAS

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    1. C. O'Muircheartaigh & P. Campanelli, 1999. "A multilevel exploration of the role of interviewers in survey non‐response," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 162(3), pages 437-446.
    2. G. Blom, Annelies, 2009. "Explaining cross-country differences in contact rates," ISER Working Paper Series 2009-08, Institute for Social and Economic Research.
    3. repec:mpr:mprres:4937 is not listed on IDEAS
    4. Lynn, Peter & S. Clarke, Paul, 2001. "Separating refusal bias and non-contact bias: evidence from UK national surveys," ISER Working Paper Series 2001-24, Institute for Social and Economic Research.
    5. repec:mpr:mprres:4780 is not listed on IDEAS
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    Cited by:

    1. Mark Hanly & Paul Clarke & Fiona Steele, 2016. "Sequence analysis of call record data: exploring the role of different cost settings," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 179(3), pages 793-808, June.
    2. Hanly, Mark & Clarke, Paul & Steele, Fiona, 2016. "Sequence analysis of call record data: exploring the role of different cost settings," LSE Research Online Documents on Economics 64896, London School of Economics and Political Science, LSE Library.
    3. Kristen Olson, 2013. "Paradata for Nonresponse Adjustment," The ANNALS of the American Academy of Political and Social Science, , vol. 645(1), pages 142-170, January.
    4. Osier, Guillaume, 2016. "Unit non-response in household wealth surveys," Statistics Paper Series 15, European Central Bank.

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