Nonresponse bias adjustments: what can process data contribute? - Annelies G. Blom (University of Essex, Institute for Social and Economic Research (ISER), 2009)
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.
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