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Thinking Clearly About Sampling and Representation With the Total Survey Error Framework

ABSTRACT

Collecting a sample that represents the population of interest well constitutes a challenge across the social and behavioural sciences. Psychology in particular frequently relies on convenience samples—most notably students and, increasingly, online participants—with a tendency to either (implicitly) assume representativeness without substantive justification, or to acknowledge a lack of it only in passing. In contrast, researchers rarely engage with the actual implications for their inferences, which undermines the generalisability of psychological findings. Critically, representativeness must be defined with respect to variables relevant to the target of inference, rather than superficial demographic diversity. Here we present the Total Survey Error (TSE) framework as a methodological tool that systematically addresses the multifaceted sources of error—particularly those related to representation—that emerge throughout the research cycle. Although TSE originated in survey research, its principles are broadly applicable to any psychological study seeking inference from sample to population. We offer practical strategies for identifying, preventing, and mitigating representation errors to improve the credibility and generalisability of psychological research.

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Posted in: Journal Article Abstracts on 08/21/2026 | Link to this post on IFP |
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