Nonresponse bias adjustments : what can process data contribute?

Blom, Annelies G.

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Document Type: Working paper
Year of publication: 2009
The title of a journal, publication series: ISER Working Paper Series
Volume: 09-21
Place of publication: Colchester
Publishing house: ISER, University of Essex
Publication language: English
Institution: Außerfakultäre Einrichtungen > Leibniz-Institut für Sozialwissenschaften (GESIS)
School of Social Sciences > Data Science (Blom 2017-2022)
Subject: 300 Social sciences, sociology, anthropology
Classification: JEL: C81 , C83,
Keywords (English): nonresponse weighting , propensity scores , post-stratification , paradata , contact data , European Social Survey
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.

Dieser Datensatz wurde nicht während einer Tätigkeit an der Universität Mannheim veröffentlicht, dies ist eine Externe Publikation.

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