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HIV survey in Mozambique: analysis with simultaneous model in contrast to separate hierarchical models

BACKGROUND: The analysis of correlated responses obtained one at a time in survey data is not as informative or as useful as modeling them simultaneously. Simultaneous modeling allows for the opportunity to evaluate the system in a more pragmatic form rather than to allow for responses that assumedl...

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Autores principales: Fang, Di, Lang, Anqi, Wilson, Jeffrey R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7395358/
https://www.ncbi.nlm.nih.gov/pubmed/32765847
http://dx.doi.org/10.1186/s13690-020-00453-8
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author Fang, Di
Lang, Anqi
Wilson, Jeffrey R.
author_facet Fang, Di
Lang, Anqi
Wilson, Jeffrey R.
author_sort Fang, Di
collection PubMed
description BACKGROUND: The analysis of correlated responses obtained one at a time in survey data is not as informative or as useful as modeling them simultaneously. Simultaneous modeling allows for the opportunity to evaluate the system in a more pragmatic form rather than to allow for responses that assumedly originated in isolation. METHODS: This research uses the Mozambique National Survey data to demonstrate the benefits of simultaneous modeling on blood test results, knowledge of HIV/AIDS, and awareness of an HIV/AIDS campaign. This simultaneous modeling also addresses the correlation inherent due to the hierarchical structure in the data collection. RESULTS: Employment and self-perceived risk of HIV/AIDS have different impact on blood test, awareness of an HIV/AIDS campaign, and knowledge of HIV/AIDS when examined simultaneously as opposed to separate modeling. CONCLUSION: Simultaneous modeling of correlated responses improves the reliability of the estimates. More importantly, it provides an opportunity to engage in cost-saving decisions when designing future surveys and make better health policies.
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spelling pubmed-73953582020-08-05 HIV survey in Mozambique: analysis with simultaneous model in contrast to separate hierarchical models Fang, Di Lang, Anqi Wilson, Jeffrey R. Arch Public Health Research BACKGROUND: The analysis of correlated responses obtained one at a time in survey data is not as informative or as useful as modeling them simultaneously. Simultaneous modeling allows for the opportunity to evaluate the system in a more pragmatic form rather than to allow for responses that assumedly originated in isolation. METHODS: This research uses the Mozambique National Survey data to demonstrate the benefits of simultaneous modeling on blood test results, knowledge of HIV/AIDS, and awareness of an HIV/AIDS campaign. This simultaneous modeling also addresses the correlation inherent due to the hierarchical structure in the data collection. RESULTS: Employment and self-perceived risk of HIV/AIDS have different impact on blood test, awareness of an HIV/AIDS campaign, and knowledge of HIV/AIDS when examined simultaneously as opposed to separate modeling. CONCLUSION: Simultaneous modeling of correlated responses improves the reliability of the estimates. More importantly, it provides an opportunity to engage in cost-saving decisions when designing future surveys and make better health policies. BioMed Central 2020-07-31 /pmc/articles/PMC7395358/ /pubmed/32765847 http://dx.doi.org/10.1186/s13690-020-00453-8 Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Fang, Di
Lang, Anqi
Wilson, Jeffrey R.
HIV survey in Mozambique: analysis with simultaneous model in contrast to separate hierarchical models
title HIV survey in Mozambique: analysis with simultaneous model in contrast to separate hierarchical models
title_full HIV survey in Mozambique: analysis with simultaneous model in contrast to separate hierarchical models
title_fullStr HIV survey in Mozambique: analysis with simultaneous model in contrast to separate hierarchical models
title_full_unstemmed HIV survey in Mozambique: analysis with simultaneous model in contrast to separate hierarchical models
title_short HIV survey in Mozambique: analysis with simultaneous model in contrast to separate hierarchical models
title_sort hiv survey in mozambique: analysis with simultaneous model in contrast to separate hierarchical models
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7395358/
https://www.ncbi.nlm.nih.gov/pubmed/32765847
http://dx.doi.org/10.1186/s13690-020-00453-8
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