Properties of the weighting cell estimator under a nonparametric response mechanism
Autor(a) principal: | |
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Data de Publicação: | 2004 |
Outros Autores: | |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UFRN |
Texto Completo: | https://repositorio.ufrn.br/jspui/handle/123456789/26222 |
Resumo: | The weighting cell estimator corrects for unit nonresponse by dividing the sample into homogeneous groups (cells) and applying a ratio correction to the respondents within each cell. Previous studies of the statistical properties of weighting cell estimators have assumed that these cells correspond to known population cells with homogeneous characteristics. In this article, we study the properties of the weighting cell estimator under a response probability model that does not require correct specification of homogeneous population cells. Instead, we assume that the response probabilities are a smooth but otherwise unspecified function of a known auxiliary variable. Under this more general model, we study the robustness of the weighting cell estimator against model misspecification. We show that, even when the population cells are unknown, the estimator is consistent with respect to the sampling design and the response model. We describe the effect of the number of weighting cells on the asymptotic properties of the estimator. Simulation experiments explore the finite sample properties of the estimator. We conclude with some guidance on how to select the size and number of cells for practical implementation of weighting cell estimation when those cells cannot be specified a priori. |
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Silva, Damião Nóbrega daOpsomer, Jean D.2018-11-28T17:19:51Z2018-11-28T17:19:51Z2004-06SILVA, Damião Nóbrega da ; OPSOMER, Jean D. Properties of the weighting cell estimator under a nonparametric response mechanism. Survey Methodology , Canadá, v. 30, n.1, p. 45-55, 2004. Disponível em: <http://www.statcan.gc.ca/pub/12-001-x/2004001/article/6993-eng.pdf >. Acesso em: 28 nov. 20181492-0921https://repositorio.ufrn.br/jspui/handle/123456789/26222engSurvey MethodologyFinite population asymptoticsQuasi-randomization inferenceWeighting cell selectionProperties of the weighting cell estimator under a nonparametric response mechanisminfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleThe weighting cell estimator corrects for unit nonresponse by dividing the sample into homogeneous groups (cells) and applying a ratio correction to the respondents within each cell. Previous studies of the statistical properties of weighting cell estimators have assumed that these cells correspond to known population cells with homogeneous characteristics. In this article, we study the properties of the weighting cell estimator under a response probability model that does not require correct specification of homogeneous population cells. Instead, we assume that the response probabilities are a smooth but otherwise unspecified function of a known auxiliary variable. Under this more general model, we study the robustness of the weighting cell estimator against model misspecification. We show that, even when the population cells are unknown, the estimator is consistent with respect to the sampling design and the response model. We describe the effect of the number of weighting cells on the asymptotic properties of the estimator. Simulation experiments explore the finite sample properties of the estimator. We conclude with some guidance on how to select the size and number of cells for practical implementation of weighting cell estimation when those cells cannot be specified a priori.info:eu-repo/semantics/openAccessreponame:Repositório Institucional da UFRNinstname:Universidade Federal do Rio Grande do Norte (UFRN)instacron:UFRNORIGINALPropertiesOfTheWeighting_2004.pdfPropertiesOfTheWeighting_2004.pdfapplication/pdf284512https://repositorio.ufrn.br/bitstream/123456789/26222/1/PropertiesOfTheWeighting_2004.pdf50a16df047308364eede7563d416f141MD51LICENSElicense.txtlicense.txttext/plain; charset=utf-81748https://repositorio.ufrn.br/bitstream/123456789/26222/2/license.txt8a4605be74aa9ea9d79846c1fba20a33MD52TEXTPropertiesOfTheWeighting_2004.pdf.txtPropertiesOfTheWeighting_2004.pdf.txtExtracted texttext/plain55451https://repositorio.ufrn.br/bitstream/123456789/26222/3/PropertiesOfTheWeighting_2004.pdf.txt55e142900ef12d330421e9db96964aabMD53THUMBNAILPropertiesOfTheWeighting_2004.pdf.jpgPropertiesOfTheWeighting_2004.pdf.jpgIM Thumbnailimage/jpeg3004https://repositorio.ufrn.br/bitstream/123456789/26222/4/PropertiesOfTheWeighting_2004.pdf.jpg591e13808c591a95793747d2fdd74980MD54TEXTPropertiesOfTheWeighting_2004.pdf.txtPropertiesOfTheWeighting_2004.pdf.txtExtracted texttext/plain55451https://repositorio.ufrn.br/bitstream/123456789/26222/3/PropertiesOfTheWeighting_2004.pdf.txt55e142900ef12d330421e9db96964aabMD53THUMBNAILPropertiesOfTheWeighting_2004.pdf.jpgPropertiesOfTheWeighting_2004.pdf.jpgIM Thumbnailimage/jpeg3004https://repositorio.ufrn.br/bitstream/123456789/26222/4/PropertiesOfTheWeighting_2004.pdf.jpg591e13808c591a95793747d2fdd74980MD54123456789/262222019-01-30 05:52:25.796oai:https://repositorio.ufrn.br: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Repositório de PublicaçõesPUBhttp://repositorio.ufrn.br/oai/opendoar:2019-01-30T08:52:25Repositório Institucional da UFRN - Universidade Federal do Rio Grande do Norte (UFRN)false |
dc.title.pt_BR.fl_str_mv |
Properties of the weighting cell estimator under a nonparametric response mechanism |
title |
Properties of the weighting cell estimator under a nonparametric response mechanism |
spellingShingle |
Properties of the weighting cell estimator under a nonparametric response mechanism Silva, Damião Nóbrega da Finite population asymptotics Quasi-randomization inference Weighting cell selection |
title_short |
Properties of the weighting cell estimator under a nonparametric response mechanism |
title_full |
Properties of the weighting cell estimator under a nonparametric response mechanism |
title_fullStr |
Properties of the weighting cell estimator under a nonparametric response mechanism |
title_full_unstemmed |
Properties of the weighting cell estimator under a nonparametric response mechanism |
title_sort |
Properties of the weighting cell estimator under a nonparametric response mechanism |
author |
Silva, Damião Nóbrega da |
author_facet |
Silva, Damião Nóbrega da Opsomer, Jean D. |
author_role |
author |
author2 |
Opsomer, Jean D. |
author2_role |
author |
dc.contributor.author.fl_str_mv |
Silva, Damião Nóbrega da Opsomer, Jean D. |
dc.subject.por.fl_str_mv |
Finite population asymptotics Quasi-randomization inference Weighting cell selection |
topic |
Finite population asymptotics Quasi-randomization inference Weighting cell selection |
description |
The weighting cell estimator corrects for unit nonresponse by dividing the sample into homogeneous groups (cells) and applying a ratio correction to the respondents within each cell. Previous studies of the statistical properties of weighting cell estimators have assumed that these cells correspond to known population cells with homogeneous characteristics. In this article, we study the properties of the weighting cell estimator under a response probability model that does not require correct specification of homogeneous population cells. Instead, we assume that the response probabilities are a smooth but otherwise unspecified function of a known auxiliary variable. Under this more general model, we study the robustness of the weighting cell estimator against model misspecification. We show that, even when the population cells are unknown, the estimator is consistent with respect to the sampling design and the response model. We describe the effect of the number of weighting cells on the asymptotic properties of the estimator. Simulation experiments explore the finite sample properties of the estimator. We conclude with some guidance on how to select the size and number of cells for practical implementation of weighting cell estimation when those cells cannot be specified a priori. |
publishDate |
2004 |
dc.date.issued.fl_str_mv |
2004-06 |
dc.date.accessioned.fl_str_mv |
2018-11-28T17:19:51Z |
dc.date.available.fl_str_mv |
2018-11-28T17:19:51Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.citation.fl_str_mv |
SILVA, Damião Nóbrega da ; OPSOMER, Jean D. Properties of the weighting cell estimator under a nonparametric response mechanism. Survey Methodology , Canadá, v. 30, n.1, p. 45-55, 2004. Disponível em: <http://www.statcan.gc.ca/pub/12-001-x/2004001/article/6993-eng.pdf >. Acesso em: 28 nov. 2018 |
dc.identifier.uri.fl_str_mv |
https://repositorio.ufrn.br/jspui/handle/123456789/26222 |
dc.identifier.issn.none.fl_str_mv |
1492-0921 |
identifier_str_mv |
SILVA, Damião Nóbrega da ; OPSOMER, Jean D. Properties of the weighting cell estimator under a nonparametric response mechanism. Survey Methodology , Canadá, v. 30, n.1, p. 45-55, 2004. Disponível em: <http://www.statcan.gc.ca/pub/12-001-x/2004001/article/6993-eng.pdf >. Acesso em: 28 nov. 2018 1492-0921 |
url |
https://repositorio.ufrn.br/jspui/handle/123456789/26222 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.publisher.none.fl_str_mv |
Survey Methodology |
publisher.none.fl_str_mv |
Survey Methodology |
dc.source.none.fl_str_mv |
reponame:Repositório Institucional da UFRN instname:Universidade Federal do Rio Grande do Norte (UFRN) instacron:UFRN |
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Universidade Federal do Rio Grande do Norte (UFRN) |
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UFRN |
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UFRN |
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Repositório Institucional da UFRN |
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