Discrete familial data consist of count or binary responses along with suitable covariates from the members of a large number of independent families, whereas discrete longitudinal data consist of similar responses and covariates collected repeatedly over a small period of time from a large number of independent individuals. As the statistical modelling of correlation structures especially for the discrete longitudinal data has not been easy, many researchers over the last two decades have used either certain ‘working’ models or mixed (familial) models for the analysis of discrete longitudinal data. Many books are also written reflecting these ‘working’ or mixed models based research. This book, however, presents a clear difference between the modelling of familial and longitudinal data. Parametric or semiparametric mixed models are used to analyze familial data, whereas parametric dynamic models are exploited to analyze the longitudinal data. Consequently, dynamic mixed models are used to analyze combined familial longitudinal data. Basic properties of the models are discussed in detail.