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Thirty-three myths and misconceptions about population data: from data capture and processing to linkage

Databases covering all individuals of a population are increasingly used for research and decision-making. The massive size of such databases is often mistaken as a guarantee for valid inferences. However, population data have characteristics that make them challenging to use. Various assumptions on...

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Autores principales: Christen, Peter, Schnell, Rainer
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Swansea University 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10454001/
https://www.ncbi.nlm.nih.gov/pubmed/37636835
http://dx.doi.org/10.23889/ijpds.v8i1.2115
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author Christen, Peter
Schnell, Rainer
author_facet Christen, Peter
Schnell, Rainer
author_sort Christen, Peter
collection PubMed
description Databases covering all individuals of a population are increasingly used for research and decision-making. The massive size of such databases is often mistaken as a guarantee for valid inferences. However, population data have characteristics that make them challenging to use. Various assumptions on population coverage and data quality are commonly made, including how such data were captured and what types of processing have been applied to them. Furthermore, the full potential of population data can often only be unlocked when such data are linked to other databases. Record linkage often implies subtle technical problems, which are easily missed. We discuss a diverse range of myths and misconceptions relevant for anybody capturing, processing, linking, or analysing population data. Remarkably, many of these myths and misconceptions are due to the social nature of data collections and are therefore missed by purely technical accounts of data processing. Many are also not well documented in scientific publications. We conclude with a set of recommendations for using population data.
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spelling pubmed-104540012023-08-26 Thirty-three myths and misconceptions about population data: from data capture and processing to linkage Christen, Peter Schnell, Rainer Int J Popul Data Sci Population Data Science Databases covering all individuals of a population are increasingly used for research and decision-making. The massive size of such databases is often mistaken as a guarantee for valid inferences. However, population data have characteristics that make them challenging to use. Various assumptions on population coverage and data quality are commonly made, including how such data were captured and what types of processing have been applied to them. Furthermore, the full potential of population data can often only be unlocked when such data are linked to other databases. Record linkage often implies subtle technical problems, which are easily missed. We discuss a diverse range of myths and misconceptions relevant for anybody capturing, processing, linking, or analysing population data. Remarkably, many of these myths and misconceptions are due to the social nature of data collections and are therefore missed by purely technical accounts of data processing. Many are also not well documented in scientific publications. We conclude with a set of recommendations for using population data. Swansea University 2023-01-31 /pmc/articles/PMC10454001/ /pubmed/37636835 http://dx.doi.org/10.23889/ijpds.v8i1.2115 Text en https://creativecommons.org/licenses/by-nc-nd/4.0/This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
spellingShingle Population Data Science
Christen, Peter
Schnell, Rainer
Thirty-three myths and misconceptions about population data: from data capture and processing to linkage
title Thirty-three myths and misconceptions about population data: from data capture and processing to linkage
title_full Thirty-three myths and misconceptions about population data: from data capture and processing to linkage
title_fullStr Thirty-three myths and misconceptions about population data: from data capture and processing to linkage
title_full_unstemmed Thirty-three myths and misconceptions about population data: from data capture and processing to linkage
title_short Thirty-three myths and misconceptions about population data: from data capture and processing to linkage
title_sort thirty-three myths and misconceptions about population data: from data capture and processing to linkage
topic Population Data Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10454001/
https://www.ncbi.nlm.nih.gov/pubmed/37636835
http://dx.doi.org/10.23889/ijpds.v8i1.2115
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