Novel statistical approaches for censored immunological data

Ballenberger, Nikolaus (2012): Novel statistical approaches for censored immunological data: analysis of cytokine and gene expression data. Dissertation, LMU München: Faculty of Medicine

Abstract

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

• Item Type: Theses (Dissertation, LMU Munich)
• Subjects: 600 Technology, Medicine; 600 Technology, Medicine > 610 Medical sciences and medicine
• Faculties: Faculty of Medicine
• Language: English
• Date of oral examination: 12. November 2012
• 1. Referee: Mutius, Erika von
• Signature of the printed copy: 0700/UMD 15242