Causal Modeling via Structural Equation Systems

Causal modeling is an informal name attached to a class of methods of multivariate analysis concerned with testing structural theories of a phenomenon. In most cases, these structural theories are intended to represent “causal” processes that give rise to observations on multivariate variables. Of course, establishment of proof regarding causality is quite likely to be beyond the capabilities of any single research study, especially those based on nonexperimental observations such as are often obtained by behavioral researchers. Thus, the name “causal modeling” is, in the strict sense, a misnomer, but the phrase adequately captures the intent of the research methodology: to hypothesize and specify in detail the process of interrelated effects operating among variables under appropriate conditions, and to test whether a relevant set of observed data is consistent with the proposed theoretical process hypothesis. Causal modeling is thus a confirmatory method, aimed at evaluating proposed theories, rather than an exploratory method, aimed at discovering theories via multivariate methods.

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