Permutation tests with application to vaccine study

Music City Center 

Permutation tests offer a robust and non-parametric approach to hypothesis testing, particularly when traditional assumptions of normality or homoscedasticity are violated. This paper explores the application of permutation testing in vaccine research, focusing on critical measures such as immunogenicity and vaccine efficacy profiles. Immunogenicity, typically assessed through antibody titers or cellular immune responses, often exhibits skewed or non-normal distributions, making traditional parametric methods less reliable. Similarly, vaccine efficacy, expressed as the reduction in disease incidence between vaccinated and unvaccinated groups, presents challenges due to complex data structures. Through simulation studies and the analysis of real-world vaccine trial data, we demonstrate how permutation tests and studentized permutation method provide a flexible and robust alternative for comparing immune response distributions and efficacy rates across treatment groups. The study also contrasts permutation tests with traditional statistical methods, highlighting the competitive performance in various scenarios and non-standard data settings.

permutation test

studentized permutation method

exact and asymptotic inference 

Biopharmaceutical Section