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Abstract:
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Researchers across the health and social sciences generally assume that observations are independent, even while relying on convenience samples that draw subjects from one or a small number of communities, schools, hospitals, etc. A paradigmatic example of this is the Framingham Heart Study (FHS). Many of the limitations of such samples are well-known, but the issue of statistical dependence due to social network ties has not previously been addressed. We show that, along with anticonservative variance estimation, this can result in spurious associations due to network dependence. Using a statistical test that we adapted from one developed for spatial autocorrelation, we test for network dependence in several of the thousands of influential papers that used FHS data. Results suggest that some of the many decades of research on health outcomes and peer influence using FHS data may suffer from spurious associations, error-prone point estimates, and anticonservative inference. These issues are not unique to the FHS; as researchers grapple with replication failures, this unacknowledged source of invalid statistical inference should be part of the conversation.
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