Investigating lived ostracism: Valid causal inference requires articulating the causal estimand

The field of ostracism research is witnessing a growing interest in understanding ostracism – being excluded and ignored – as a lived experience outside of the laboratory context. How do researchers draw valid causal conclusions about naturally occurring experiences of ostracism without relying on experimental designs? In this article, we draw on insights from the well-established causal inference framework to emphasize a critical step for strengthening causal rigor: stating the causal estimand. Using an intuitive example, we illustrate what a causal estimand is, how to define it, and why it matters. With this article, we encourage readers to think clearly about causal estimands before conducting any data analysis. This conceptual step holds the potential for enhancing the rigor and precision of research studying ostracism as a naturally occurring phenomenon.

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Publication Details

Published
2025-08-29
DOI
https://doi.org/10.31234/osf.io/6s7d8_v2
Primary Topic
Death Anxiety and Social Exclusion
Type
article
Field-Weighted Citation Impact
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Investigating lived ostracism: Valid causal inference requires articulating the causal estimand

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Death Anxiety and Social Exclusion
article

Investigating lived ostracism: Valid causal inference requires articulating the causal estimand

Olga Stavrova, Wen Wei Loh, Dongning Ren, Eric van Dijk, Ilja van Beest
article en

Abstract

The field of ostracism research is witnessing a growing interest in understanding ostracism – being excluded and ignored – as a lived experience outside of the laboratory context. How do researchers draw valid causal conclusions about naturally occurring experiences of ostracism without relying on experimental designs? In this article, we draw on insights from the well-established causal inference framework to emphasize a critical step for strengthening causal rigor: stating the causal estimand. Using an intuitive example, we illustrate what a causal estimand is, how to define it, and why it matters. With this article, we encourage readers to think clearly about causal estimands before conducting any data analysis. This conceptual step holds the potential for enhancing the rigor and precision of research studying ostracism as a naturally occurring phenomenon.

Maastricht University (NL)
Openalex Percentile: Top 74%
Death Anxiety and Social Exclusion
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