Common Misconceptions about Population Data

• URL: http://arxiv.org/abs/2112.10912v1
• Date: Mon, 20 Dec 2021 23:54:49 GMT
• Title: Common Misconceptions about Population Data
• Authors: Peter Christen and Rainer Schnell
• Abstract summary: This article discusses a diverse range of misconceptions about population data that we believe anybody who works with such data needs to be aware of. The massive size of such databases is often mistaken as a guarantee for valid inferences on the population of interest. We conclude with a set of recommendations for inference when using population data.
• Score: 5.606904856295946
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Databases covering all individuals of a population are increasingly used for research studies in domains ranging from public health to the social sciences. There is also growing interest by governments and businesses to use population data to support data-driven decision making. The massive size of such databases is often mistaken as a guarantee for valid inferences on the population of interest. However, population data have characteristics that make them challenging to use, including various assumptions being made how such data were collected 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, a process that adds fresh challenges. This article discusses a diverse range of misconceptions about population data that we believe anybody who works with such data needs to be aware of. Many of these misconceptions are not well documented in scientific publications but only discussed anecdotally among researchers and practitioners. We conclude with a set of recommendations for inference when using population data.

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