Redefining Representativeness of a Sample in Causal Terms

Abstract

Rationale: Despite its crucial role, sample representativeness remains a controversial topic in the methodology of medical science. There is an ongoing debate not only about how best to define and ensure the representativeness of a sample (e.g., Rudolph et al. 2023; Porta 2016), but also about whether representativeness is worth pursuing at all (e.g., Rothman et al. 2013).

Aims and objectives: Our aim is to construct a formalised, precise, and practical conceptualisation of sample representativeness.

Methods: We employ the established framework of causal Bayesian networks to develop such a conceptualisation.

Results: We propose a precise formal definition of sample representativeness that translates into clear and actionable methodological guidance. Additionally, we provide examples and a checklist to illustrate the application of the proposed conceptualisation.

Conclusion: We believe that the presented definition will facilitate further discussion of the issue of representativeness and prove useful to scientists in practice.

Figure 1

Simple exemplary causal model.

Figure 2

Causal structures of the sample (a) and the target population (b).