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Validation of non-participation bias methodology based on record-linked Finnish register-based health survey data: a protocol paper

INTRODUCTION: Decreasing participation levels in health surveys pose a threat to the validity of estimates intended to be representative of their target population. If participants and non-participants differ systematically, the results may be biased. The application of traditional non-response adju...

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Autores principales: McMinn, Megan A, Martikainen, Pekka, Gorman, Emma, Rissanen, Harri, Härkänen, Tommi, Tolonen, Hanna, Leyland, Alastair H, Gray, Linsay
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6500270/
https://www.ncbi.nlm.nih.gov/pubmed/30948596
http://dx.doi.org/10.1136/bmjopen-2018-026187
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author McMinn, Megan A
Martikainen, Pekka
Gorman, Emma
Rissanen, Harri
Härkänen, Tommi
Tolonen, Hanna
Leyland, Alastair H
Gray, Linsay
author_facet McMinn, Megan A
Martikainen, Pekka
Gorman, Emma
Rissanen, Harri
Härkänen, Tommi
Tolonen, Hanna
Leyland, Alastair H
Gray, Linsay
author_sort McMinn, Megan A
collection PubMed
description INTRODUCTION: Decreasing participation levels in health surveys pose a threat to the validity of estimates intended to be representative of their target population. If participants and non-participants differ systematically, the results may be biased. The application of traditional non-response adjustment methods, such as weighting, can fail to correct for such biases, as estimates are typically based on the sociodemographic information available. Therefore, a dedicated methodology to infer on non-participants offers advancement by employing survey data linked to administrative health records, with reference to data on the general population. We aim to validate such a methodology in a register-based setting, where individual-level data on participants and non-participants are available, taking alcohol consumption estimation as the exemplar focus. METHODS AND ANALYSIS: We made use of the selected sample of the Health 2000 survey conducted in Finland and a separate register-based sample of the contemporaneous population, with follow-up until 2012. Finland has nationally representative administrative and health registers available for individual-level record linkage to the Health 2000 survey participants and invited non-participants, and the population sample. By comparing the population sample and the participants, synthetic observations representing the non-participants may be generated, as per the developed methodology. We can compare the distribution of the synthetic non-participants with the true distribution from the register data. Multiple imputation was then used to estimate alcohol consumption based on both the actual and synthetic data for non-participants, and the estimates can be compared to evaluate the methodology’s performance. ETHICS AND DISSEMINATION: Ethical approval and access to the Health 2000 survey data and data from administrative and health registers have been given by the Health 2000 Scientific Advisory Board, Statistics Finland and the National Institute for Health and Welfare. The outputs will include two publications in public health and statistical methodology journals and conference presentations.
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spelling pubmed-65002702019-05-21 Validation of non-participation bias methodology based on record-linked Finnish register-based health survey data: a protocol paper McMinn, Megan A Martikainen, Pekka Gorman, Emma Rissanen, Harri Härkänen, Tommi Tolonen, Hanna Leyland, Alastair H Gray, Linsay BMJ Open Research Methods INTRODUCTION: Decreasing participation levels in health surveys pose a threat to the validity of estimates intended to be representative of their target population. If participants and non-participants differ systematically, the results may be biased. The application of traditional non-response adjustment methods, such as weighting, can fail to correct for such biases, as estimates are typically based on the sociodemographic information available. Therefore, a dedicated methodology to infer on non-participants offers advancement by employing survey data linked to administrative health records, with reference to data on the general population. We aim to validate such a methodology in a register-based setting, where individual-level data on participants and non-participants are available, taking alcohol consumption estimation as the exemplar focus. METHODS AND ANALYSIS: We made use of the selected sample of the Health 2000 survey conducted in Finland and a separate register-based sample of the contemporaneous population, with follow-up until 2012. Finland has nationally representative administrative and health registers available for individual-level record linkage to the Health 2000 survey participants and invited non-participants, and the population sample. By comparing the population sample and the participants, synthetic observations representing the non-participants may be generated, as per the developed methodology. We can compare the distribution of the synthetic non-participants with the true distribution from the register data. Multiple imputation was then used to estimate alcohol consumption based on both the actual and synthetic data for non-participants, and the estimates can be compared to evaluate the methodology’s performance. ETHICS AND DISSEMINATION: Ethical approval and access to the Health 2000 survey data and data from administrative and health registers have been given by the Health 2000 Scientific Advisory Board, Statistics Finland and the National Institute for Health and Welfare. The outputs will include two publications in public health and statistical methodology journals and conference presentations. BMJ Publishing Group 2019-04-04 /pmc/articles/PMC6500270/ /pubmed/30948596 http://dx.doi.org/10.1136/bmjopen-2018-026187 Text en © Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY. Published by BMJ. This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See: https://creativecommons.org/licenses/by/4.0/.
spellingShingle Research Methods
McMinn, Megan A
Martikainen, Pekka
Gorman, Emma
Rissanen, Harri
Härkänen, Tommi
Tolonen, Hanna
Leyland, Alastair H
Gray, Linsay
Validation of non-participation bias methodology based on record-linked Finnish register-based health survey data: a protocol paper
title Validation of non-participation bias methodology based on record-linked Finnish register-based health survey data: a protocol paper
title_full Validation of non-participation bias methodology based on record-linked Finnish register-based health survey data: a protocol paper
title_fullStr Validation of non-participation bias methodology based on record-linked Finnish register-based health survey data: a protocol paper
title_full_unstemmed Validation of non-participation bias methodology based on record-linked Finnish register-based health survey data: a protocol paper
title_short Validation of non-participation bias methodology based on record-linked Finnish register-based health survey data: a protocol paper
title_sort validation of non-participation bias methodology based on record-linked finnish register-based health survey data: a protocol paper
topic Research Methods
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6500270/
https://www.ncbi.nlm.nih.gov/pubmed/30948596
http://dx.doi.org/10.1136/bmjopen-2018-026187
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