Novel statistical approaches for censored immunological data

For several immune-mediated diseases, immunological analysis will
become more complex in the future with datasets in which cytokine
and gene expression data play a major role. These data have certain
characteristics that require sophisticated statistical analysis
such as strategies for non-normal distribution and censoring.
Additionally, complex and multiple immunological relationships need
to be adjusted for potential confounding and interaction effects.I
aimed to introduce and apply different methods for statistical
analysis of non-normal censored cytokine and gene expression data.
Furthermore, I assessed the performance and accuracy of a novel
regression approach in order to allow adjusting for covariates and
potential confounding