%0 Journal Article %1 Christen2023-ou %A Christen, Peter %A Schnell, Rainer %D 2023 %I Swansea University %J Int. J. Popul. Data Sci. %K administrative data editing errors linkage personal quality record %N 1 %P 2115 %T Thirty-three myths and misconceptions about population data: from data capture and processing to linkage %V 8 %X 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.

@article{Christen2023-ou, 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.}, added-at = {2025-01-08T12:06:15.000+0100}, author = {Christen, Peter and Schnell, Rainer}, biburl = {https://puma.scadsai.uni-leipzig.de/bibtex/26c48aa3f6011c7051b82f969e46d7a43/scadsfct}, interhash = {54b31cb4d33c16276fb1a97b74d4c168}, intrahash = {6c48aa3f6011c7051b82f969e46d7a43}, journal = {Int. J. Popul. Data Sci.}, keywords = {administrative data editing errors linkage personal quality record}, language = {en}, month = jan, number = 1, pages = 2115, publisher = {Swansea University}, timestamp = {2025-01-08T12:06:15.000+0100}, title = {Thirty-three myths and misconceptions about population data: from data capture and processing to linkage}, volume = 8, year = 2023 }