ABSTRACT
This chapter presents statistical models that consider multiple paths in predicting the formation of Flashbulb memories (FBMs). The most common statistical tool used for testing models predicting FBM formation is called Structural Equation Modelling (SEM). The main advantage of using the SEM approach is that it allows for the theorized relationships among FBM variables to be tested. The chapter compares theoretically-founded models with data from events in which FBMs were observed, and provides two levels of information: the overall fit and the relationships among predictors. It presents the basic principles, the type of design adopted to assess FBMs, the main empirical findings that were obtained using these models, the strengths and limitations regarding the model itself and its theoretical background, its ability to fit the data, and the appropriateness of events that were analyzed for testing these models. A general consensus is found in the literature about the main emotional, cognitive, and social factors affecting FBM.
