ABSTRACT
This chapter describes models that are often referred to as ‘causal models’, although this term is somewhat misleading as many of the models already presented can be considered as providing evidence of ‘causality’ if theory dictates that the variables are not merely associated but are causally connected. Furthermore, models for longitudinal data analysis described in the next two chapters are also regarded as providing greater insights and understanding of underlying causal mechanisms and processes. Perhaps the models described in this chapter have attracted the term causal models because the researcher often sets out the relationships and causal connections diagrammatically. Another distinguishing feature of models described in this chapter is that the causal mechanisms considered often lead to a model entailing more than one equation which need to be considered jointly; hence the other term used to describe such models, simultaneous equation models.
