ArticleInternational journal of population data science2023
Thirty-three myths and misconceptions about population data: from data capture and processing to linkage.
Article in International journal of population data science, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed.
- Evaluating the "right@home" randomized trial of nurse home visiting using linked administrative data at school transition.International journal of population data science · 2024Trial
- Long-Term Impact of Historical BCG Vaccination Policies on Parkinson's Disease Risk: A Hypothesis-Generating Retrospective Cohort Analysis.Biomedicines · 2026Article
- Data Resource Profile: Australia's Person Level Integrated Data Asset (PLIDA).International journal of epidemiology · 2026Article
- Big Data in the Assessment of Medication Safety in Pregnancy: Opportunities and Challenges.Paediatric drugs · 2025Article
- Recommendations for Improving Surveillance of Congenital Anomalies in Europe Using Healthcare Databases.Paediatric and perinatal epidemiology · 2025Article
- Leveraging Administrative Health Databases to Address Health Challenges in Farming Populations: Scoping Review and Bibliometric Analysis (1975-2024).JMIR public health and surveillance · 2025Article
- Datagraphy: toward a systematic approach to dataset discovery.GigaScience · 2025Article
- Child welfare worker perspectives on documentation and case recording practices in Canada: A mixed-methods study protocol.PloS one · 2025Article
- Public sector health analytics capacity before and after Covid-19: A case study of manager perspectives in New Brunswick, Canada.International journal of population data science · 2024Article
- Secondary use of routinely collected administrative health data for epidemiologic research: Answering research questions using data collected for a different purpose.International journal of population data science · 2024Article
- Exploring machine learning algorithms for predicting fertility preferences among reproductive age women in Nigeria.Frontiers in digital health · 2024Article
- CIDACS' efforts towards an inclusive and dialogic data governance in Brazil: a focused literature review.International journal of population data science · 2024Review
- Simulated data for census-scale entity resolution research without privacy restrictions: a large-scale dataset generated by individual-based modeling.Gates open research · 2024Article
- From secondary data to Population Data Science: remembering 40 years of scientific production within CSP pages.Cadernos de saude publica · 2024Article
- UK research data resources based on primary care electronic health records: review and summary for potential users.BJGP open · 2023Article
- Evaluation of Survey Nonresponse in Measuring Cardiometabolic Health Risk Factors and Outcomes among Sexual Minority Populations: A National Data Linkage Analysis.International journal of environmental research and public health · 2023Article
- Adapting historical clinical genetic test records for anonymised data linkage: obstacles and opportunities.International journal of population data science · 2023Article
- Understanding data provenance when using electronic medical records for research: Lessons learned from the Deliver Primary Healthcare Information (DELPHI) database.International journal of population data science · 2023Article
- Article
- Data resource profile: the ORIGINS project databank: a collaborative data resource for investigating the developmental origins of health and disease.International journal of population data science · 2023Article
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2 authors.
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Abstract
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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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.