Titlebook: Statistics in Clinical and Observational Vaccine Studies; Jozef Nauta Book 2020Latest edition Springer Nature Switzerland AG 2020 Vaccine

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Vaccine Effectiveness Studiesonfounding is and how it can be eliminated. Many vaccine effectiveness studies have a so-called case-referent design. The key idea of these designs is clarified, and the major case-referent designs—including the popular test-negative design—are inspected. The important but difficult to grasp differe

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Meta-Analysis of Vaccine Effectiveness Studiesl test to compare vaccine effectiveness estimates exists, as well as a powerful regression method known as meta-regression. It is demonstrated how these comparative analyses, as well as non-comparative analyses according to, for example, the DerSimonian–Laird method, can be conducted using simple SA

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Immune Correlates of Protectionre widely used as surrogate endpoints for vaccine efficacy. The function specifying the relationship between immunogenicity values and the probability of protection against infection is called the protection curve. It is demonstrated how the parameters of the protection curve can be estimated from b

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Vaccine Safetyng very rare but serious adverse vaccine reactions to light. In this chapter, some major statistical aspects of vaccine safety are addressed. Vaccine safety surveillance is briefly discussed, and a recent vaccine safety controversy is recalled. The notorious problem of vaccine safety and multiplicit

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Vaccine Equivalence and Non-inferiority Trialsmula is presented which can be used to decide if the lot sample sizes guarantee that the actual type I error rate of the trial is sufficiently close to the nominal level. The chapter is concluded with a discussion of sample size estimation for vaccine equivalence and non-inferiority trials, including lot consistency trials.

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Vaccine Effectiveness Studiesnce between cumulative reference sampling and incidence sampling is explained. Next, adjusted data analysis to control for confounding, either by means of stratification or regression, is discussed. The chapter concludes with considerations on how to represent and select confounders in a regression model.

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Adjusting for Imbalance in Pre-Vaccination Stater the standard deviation of the error term. In this chapter, a solution to this problem is offered. It is shown that the heteroscedasticity can be modelled. A variance model is derived, and it is demonstrated how this model can be fitted with SAS.