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Adjusting for Imbalance in Pre-Vaccination State

  • Jozef Nauta
Chapter
  • 32 Downloads
Part of the Springer Series in Pharmaceutical Statistics book series (SSPS)

Abstract

Pre-vaccination or baseline antibody levels need not to be zero. Examples of infectious diseases for which this can be the case are tetanus, diphtheria, pertussis and tick-borne encephalitis. Imbalance in pre-vaccination state, i.e. a difference in baseline antibody levels between vaccine groups, can complicate the interpretation of a difference in post-vaccination antibody values. A standard approach to this problem is analysis of covariance. But in case of antibody values, one of the assumptions underlying this analysis, homoscedasticity, is not met. The larger the baseline value, the smaller 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.

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Jozef Nauta
    • 1
  1. 1.AmsterdamThe Netherlands

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