<p>"This book is a comprehensive state-of-the-art treatment of joint models for time-to-event and longitudinal data with numerous applications to real-world problems. … [T]his book is a comprehensive review of the existing literature on joint models, including most extensions of these models, fully parametric or not, for multiple events and multiple markers with a special focus on missingness problems and details about various estimation methods. By emphasizing the most advanced methods, this book usefully completes existing monographs on joint models and will be a helpful reference book for researchers in biostatistics and experienced statisticians, while applied statisticians could also be interested thanks to the numerous examples of real data analyses."<br />—Helene Jacqmin-Gadda, University of Bordeaux, in <i>Biometrics</i>, March 2018</p><p>"This book provides an extensive survey of research performed on the subject of joint models in longitudinal and time-to-event data. … The authors’ expertise in this area shines through their careful attention to detail in presenting the wide variety of settings in which these models can be applied. Overall, I consider the book to be a valuable and rich resource for introducing and promoting this relatively new area of research. … Where this book primarily succeeds is in the great care taken by the authors in walking through the necessary details of these joint models and the breadth of topics they cover. When topics are left out, the authors refer to a large body of literature to which the interested reader can look to further their understanding. … <br />I would recommend it either as a handy reference for researchers or as a graduate level reference text in a specialized course … [I]t is truly rich with useful content that can be extracted and applied with due diligence. …. I certainly consider it a valuable addition to my bookshelf for personal reference and, should the need arise, I would be happy to refer it to</p>