Gerhard Tutz is a professor of statistics at the Department of Statistics at the University of Munich. He has published several books with Springer.Matthias Schmid is a professor of Medical Biometry, Informatics and Epidemiology at the University of Bonn. He received his diploma (2004) and his Ph.D. (2007) in statistics at the University of Munich and his habilitation (2012) in biostatistics at the University of Erlangen. Before working in Bonn, he was professor of computational statistics at the Department of Statistics at the University of Munich (2013-2014).

“Modeling Discrete Time-to-Event Data provides an excellent overview of a field that is underrepresented in the literature. At what it aims to do, striking a balance between theory and practice, this book does a great job. Its readers will understand not only what to do, but also how to do it. I believe that this book can easily find a place on the shelf of statisticians who have an interest in survival analysis.” (Theodor Adrian Balan, Biometrical Journal, Vol. 61 (1), January, 2019)​

• Introduction.- The Life Table.- Basic Regression Models.- Evaluation and Model Choice.- Nonparametric Modelling and Smooth Effects.- Tree-Based Approaches.- High-Dimensional Models - Structuring and Selection of Predictors.- Competing Risks Models.- Multiple-Spell Analysis.- Frailty Models and Heterogeneity.- Multiple-Spell Analysis.- List of Examples.- Bibliography.- Subject Index.- Author Index.

Gerhard Tutz is a professor of statistics at the Department of Statistics at the University of Munich. He has published several books with Springer.Matthias Schmid is a professor of Medical Biometry, Informatics and Epidemiology at the University of Bonn. He received his diploma (2004) and his Ph.D. (2007) in statistics at the University of Munich and his habilitation (2012) in biostatistics at the University of Erlangen. Before working in Bonn, he was professor of computational statistics at the Department of Statistics at the University of Munich (2013-2014).

“Modeling Discrete Time-to-Event Data provides an excellent overview of a field that is underrepresented in the literature. At what it aims to do, striking a balance between theory and practice, this book does a great job. Its readers will understand not only what to do, but also how to do it. I believe that this book can easily find a place on the shelf of statisticians who have an interest in survival analysis.” (Theodor Adrian Balan, Biometrical Journal, Vol. 61 (1), January, 2019)​

• Introduction.- The Life Table.- Basic Regression Models.- Evaluation and Model Choice.- Nonparametric Modelling and Smooth Effects.- Tree-Based Approaches.- High-Dimensional Models - Structuring and Selection of Predictors.- Competing Risks Models.- Multiple-Spell Analysis.- Frailty Models and Heterogeneity.- Multiple-Spell Analysis.- List of Examples.- Bibliography.- Subject Index.- Author Index.

Gerhard Tutz is a professor of statistics at the Department of Statistics at the University of Munich. He has published several books with Springer.Matthias Schmid is a professor of Medical Biometry, Informatics and Epidemiology at the University of Bonn. He received his diploma (2004) and his Ph.D. (2007) in statistics at the University of Munich and his habilitation (2012) in biostatistics at the University of Erlangen. Before working in Bonn, he was professor of computational statistics at the Department of Statistics at the University of Munich (2013-2014).

“Modeling Discrete Time-to-Event Data provides an excellent overview of a field that is underrepresented in the literature. At what it aims to do, striking a balance between theory and practice, this book does a great job. Its readers will understand not only what to do, but also how to do it. I believe that this book can easily find a place on the shelf of statisticians who have an interest in survival analysis.” (Theodor Adrian Balan, Biometrical Journal, Vol. 61 (1), January, 2019)​

• Introduction.- The Life Table.- Basic Regression Models.- Evaluation and Model Choice.- Nonparametric Modelling and Smooth Effects.- Tree-Based Approaches.- High-Dimensional Models - Structuring and Selection of Predictors.- Competing Risks Models.- Multiple-Spell Analysis.- Frailty Models and Heterogeneity.- Multiple-Spell Analysis.- List of Examples.- Bibliography.- Subject Index.- Author Index.