Models for Incomplete and Clustered Data with Applications in Clinical Trials and Health Economic Studies

Abstract

In this thesis, we introduced and explored different modeling techniques for incomplete and/or clustered data. In part I of the thesis, models to handle incomplete data are explored, while in part II of the thesis a dataset concerning pneumococcal disease in a health economic context was analyzed. In the following sections, some concluding remarks are presented.