Exploring unobserved household living conditions in multilevel choice modeling: an application to contraceptive adoption by Indian women
Autor(a) principal: | |
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Data de Publicação: | 2018 |
Outros Autores: | |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10071/16096 |
Resumo: | This research analyzes the effect of the poverty-wealth dimension on contraceptive adoption by Indian women when no direct measures of income/expenditures are available to use as covariates. The index-Household Living Conditions (HLC)-is based on household assets and dwelling characteristics and is computed by an item response model simultaneously with the choice model in a new single-step approach. That is, the HLC indicator is treated as a latent covariate measured by a set of items, it depends on a set of concomitant variables, and explains contraceptive choices in a probit regression. Additionally, the model accounts for complex survey design and sample weights in a multilevel framework. Regarding our case study on contraceptive adoption by Indian women, results show that women with better household living conditions tend to adopt contraception more often than their counterparts. This effect is significant after controlling other factors such as education, caste, and religion. The external validation of the indicator shows that it can also be used at aggregate levels of analysis (e.g., county or state) whenever no other indicators of household living conditions are available. |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Exploring unobserved household living conditions in multilevel choice modeling: an application to contraceptive adoption by Indian womenThis research analyzes the effect of the poverty-wealth dimension on contraceptive adoption by Indian women when no direct measures of income/expenditures are available to use as covariates. The index-Household Living Conditions (HLC)-is based on household assets and dwelling characteristics and is computed by an item response model simultaneously with the choice model in a new single-step approach. That is, the HLC indicator is treated as a latent covariate measured by a set of items, it depends on a set of concomitant variables, and explains contraceptive choices in a probit regression. Additionally, the model accounts for complex survey design and sample weights in a multilevel framework. Regarding our case study on contraceptive adoption by Indian women, results show that women with better household living conditions tend to adopt contraception more often than their counterparts. This effect is significant after controlling other factors such as education, caste, and religion. The external validation of the indicator shows that it can also be used at aggregate levels of analysis (e.g., county or state) whenever no other indicators of household living conditions are available.Public Library of Science2018-06-11T16:18:44Z2018-01-01T00:00:00Z20182018-06-11T09:41:14Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10071/16096eng1932-620310.1371/journal.pone.0191784Dias, J. G.de Oliveira, I. T.info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-07-25T17:35:13ZPortal AgregadorONG |
dc.title.none.fl_str_mv |
Exploring unobserved household living conditions in multilevel choice modeling: an application to contraceptive adoption by Indian women |
title |
Exploring unobserved household living conditions in multilevel choice modeling: an application to contraceptive adoption by Indian women |
spellingShingle |
Exploring unobserved household living conditions in multilevel choice modeling: an application to contraceptive adoption by Indian women Dias, J. G. |
title_short |
Exploring unobserved household living conditions in multilevel choice modeling: an application to contraceptive adoption by Indian women |
title_full |
Exploring unobserved household living conditions in multilevel choice modeling: an application to contraceptive adoption by Indian women |
title_fullStr |
Exploring unobserved household living conditions in multilevel choice modeling: an application to contraceptive adoption by Indian women |
title_full_unstemmed |
Exploring unobserved household living conditions in multilevel choice modeling: an application to contraceptive adoption by Indian women |
title_sort |
Exploring unobserved household living conditions in multilevel choice modeling: an application to contraceptive adoption by Indian women |
author |
Dias, J. G. |
author_facet |
Dias, J. G. de Oliveira, I. T. |
author_role |
author |
author2 |
de Oliveira, I. T. |
author2_role |
author |
dc.contributor.author.fl_str_mv |
Dias, J. G. de Oliveira, I. T. |
description |
This research analyzes the effect of the poverty-wealth dimension on contraceptive adoption by Indian women when no direct measures of income/expenditures are available to use as covariates. The index-Household Living Conditions (HLC)-is based on household assets and dwelling characteristics and is computed by an item response model simultaneously with the choice model in a new single-step approach. That is, the HLC indicator is treated as a latent covariate measured by a set of items, it depends on a set of concomitant variables, and explains contraceptive choices in a probit regression. Additionally, the model accounts for complex survey design and sample weights in a multilevel framework. Regarding our case study on contraceptive adoption by Indian women, results show that women with better household living conditions tend to adopt contraception more often than their counterparts. This effect is significant after controlling other factors such as education, caste, and religion. The external validation of the indicator shows that it can also be used at aggregate levels of analysis (e.g., county or state) whenever no other indicators of household living conditions are available. |
publishDate |
2018 |
dc.date.none.fl_str_mv |
2018-06-11T16:18:44Z 2018-01-01T00:00:00Z 2018 2018-06-11T09:41:14Z |
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.uri.fl_str_mv |
http://hdl.handle.net/10071/16096 |
url |
http://hdl.handle.net/10071/16096 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
1932-6203 10.1371/journal.pone.0191784 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Public Library of Science |
publisher.none.fl_str_mv |
Public Library of Science |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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RCAAP |
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RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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1777303991753900032 |