It is important for dental researchers to have a general idea of the different types of data that can be collected from a study and the available statistical tools that can be used with such data. By knowing about what is available, researchers will have an informed idea of the types of studies that should be conducted, the data that should be collected, and the proper statistical methods for analyzing collected data. In the first part of this general overview of statistical methods, we walked through the various types of data that traditional statistical techniques, such as t tests and linear regression, can handle. In this second part, we explore more complex types of data that traditional statistical techniques are unable to handle. Specifically, we discuss longitudinal and time-to-event data because both occur frequently in dental studies and require special modeling techniques in order to analyze correctly. Using two different simulated dental datasets, the proper application of techniques such as repeated measures ANOVA, linear mixed modeling, generalized estimating equations, log-rank test, and Cox proportional hazards models are discussed and illustrated in depth.