Article

Synthetic Longitudinal Tabular Data Generation via Copula

2026-08-07

Abstract excerpt

Synthetic data generation is increasingly used to enable data sharing and secondary analysis while protecting participant privacy, particularly for longitudinal tabular health data, where repeated measures per subject create within-subject dependence that most synthetic data methods are not designed to preserve. Existing generative methods, particularly generative adversarial network (GAN)-based approaches, can mo...

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Literature Corpus work: 73f00372-bb80-560d-a114-258eba77cd7a
DOI: 10.64898/2026.08.03.742474

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