During the last decades, there has been an explosion in computation and information technology. This development comes with an expansion of complex observational studies and clinical trials in a variety of fields such as medicine, biology, epidemiology, sociology, and economics, among many others, which involve the collection of large amounts of data on subjects or organisms over time. The goal of such studies can be formulated as the estimation of a finite dimensional parameter of the population distribution corresponding to the observed time-dependent process. Such estimation problems arise in survival analysis, causal inference, and regression analysis. This book provides a fundamental statistical framework for the analysis of complex longitudinal data. It offers the first comprehensive description of optimal estimation techniques based on time-dependent data structures subject to informative factors.