Oversampling in Relation to Differential Regional Response Rates

Response rates of face-to-face surveys often show regional variation. In larger cities e.g., response typically will be lower than in smaller villages. Following current survey practices, substitution of survey non-respondents is no longer recommended. In order to achieve an adequate regional repres...

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Main Authors: Jan Pickery, Ann Carton
Format: Article
Language:English
Published: European Survey Research Association 2008-06-01
Series:Survey Research Methods
Subjects:
Online Access:https://ojs.ub.uni-konstanz.de/srm/article/view/656
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author Jan Pickery
Ann Carton
author_facet Jan Pickery
Ann Carton
author_sort Jan Pickery
collection DOAJ
description Response rates of face-to-face surveys often show regional variation. In larger cities e.g., response typically will be lower than in smaller villages. Following current survey practices, substitution of survey non-respondents is no longer recommended. In order to achieve an adequate regional representation of the population in a survey, differential regional oversampling can be an option. We show how regional ineligible rates and response rates of previous surveys can be used in a multilevel analysis to obtain residuals that form the basis for the computation of an ineligible correction and a regional oversampling factor for subsequent surveys. We argue that this oversampling design is a good alternative or complement to nonresponse weighting. We illustrate our approach with the sampling procedure used for the last edition of the yearly survey on social and cultural changes in the Flemish region.
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spelling doaj.art-a4bba8ef726549778a081315596e30782022-12-22T04:02:32ZengEuropean Survey Research AssociationSurvey Research Methods1864-33612008-06-012210.18148/srm/2008.v2i2.6561692Oversampling in Relation to Differential Regional Response RatesJan Pickery0Ann Carton1Research Centre of the Flemish GovernmentResearch Centre of the Flemish GovernmentResponse rates of face-to-face surveys often show regional variation. In larger cities e.g., response typically will be lower than in smaller villages. Following current survey practices, substitution of survey non-respondents is no longer recommended. In order to achieve an adequate regional representation of the population in a survey, differential regional oversampling can be an option. We show how regional ineligible rates and response rates of previous surveys can be used in a multilevel analysis to obtain residuals that form the basis for the computation of an ineligible correction and a regional oversampling factor for subsequent surveys. We argue that this oversampling design is a good alternative or complement to nonresponse weighting. We illustrate our approach with the sampling procedure used for the last edition of the yearly survey on social and cultural changes in the Flemish region.https://ojs.ub.uni-konstanz.de/srm/article/view/656sample designunit nonresponsemultilevel analysis
spellingShingle Jan Pickery
Ann Carton
Oversampling in Relation to Differential Regional Response Rates
Survey Research Methods
sample design
unit nonresponse
multilevel analysis
title Oversampling in Relation to Differential Regional Response Rates
title_full Oversampling in Relation to Differential Regional Response Rates
title_fullStr Oversampling in Relation to Differential Regional Response Rates
title_full_unstemmed Oversampling in Relation to Differential Regional Response Rates
title_short Oversampling in Relation to Differential Regional Response Rates
title_sort oversampling in relation to differential regional response rates
topic sample design
unit nonresponse
multilevel analysis
url https://ojs.ub.uni-konstanz.de/srm/article/view/656
work_keys_str_mv AT janpickery oversamplinginrelationtodifferentialregionalresponserates
AT anncarton oversamplinginrelationtodifferentialregionalresponserates