November 18, 2025Open Access

Inferential Z-Test Validation of Dual Structural Bias in Cancer Risk Assessment within Large COVID-19 Vaccine Cohorts

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Inferential validation reveals selection bias in cancer risk in COVID-19 vaccine cohorts, indicating critical flaws in demographic representation.

Causal chain validation confirmed significant selection bias in cancer risk assessment, questioning the data's reliability.
The Z-Test identified a substantial discrepancy in cancer incidence rates among non-vaccinated individuals aged 65 and over.
Statistical analysis underscored the need for rigorous validation against national standards before modeling risks.
Findings highlight the critical importance of addressing structural biases in health data to ensure accurate risk assessment.

Roccetti Marco (2025) studied this question.

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Inferential validation reveals selection bias in cancer risk in COVID-19 vaccine cohorts, indicating critical flaws in demographic representation.