Thesis/Theses examined by Kneib, Thomas

Köhler, Meike (2017): Flexible Bayesian joint models for longitudinal biomarkers and time-to-event outcomes with applications to type 1 diabetes research. Dissertation, LMU München: Faculty of Mathematics, Computer Science and Statistics

Cederbaum, Jona (2017): Functional linear mixed models for complex correlation structures and general sampling grids. Dissertation, LMU München: Faculty of Mathematics, Computer Science and Statistics

Schmidt, Paul (2017): Bayesian inference for structured additive regression models for large-scale problems with applications to medical imaging. Dissertation, LMU München: Faculty of Mathematics, Computer Science and Statistics

Möst, Lisa (2015): Conditional transformation models: interpretable parametrisations and censoring. Dissertation, LMU München: Faculty of Mathematics, Computer Science and Statistics

Schulze Waltrup, Linda (2015): Extensions of semiparametric expectile regression. Dissertation, LMU München: Faculty of Mathematics, Computer Science and Statistics

Oelker, Margret-Ruth (2015): Penalized regression for discrete structures. Dissertation, LMU München: Faculty of Mathematics, Computer Science and Statistics

Obermeier, Viola (2014): Flexible distributed lag models and their application to geophysical data. Dissertation, LMU München: Faculty of Mathematics, Computer Science and Statistics

Konrath, Susanne (2013): Bayesian regularization in regression models for survival data. Dissertation, LMU München: Faculty of Mathematics, Computer Science and Statistics

Heinzl, Felix (2013): Clustering in linear and additive mixed models. Dissertation, LMU München: Faculty of Mathematics, Computer Science and Statistics

Kalus, Stefanie (2012): Biostatistical modeling and analysis of combined fMRI and EEG measurements. Dissertation, LMU München: Faculty of Mathematics, Computer Science and Statistics

Scheipl, Fabian (2011): Bayesian Regularization and Model Choice in Structured Additive Regression. Dissertation, LMU München: Faculty of Mathematics, Computer Science and Statistics