Abstract
To incorporate causal thinking into statistical modelling, we need methods which can explicitly formulate the causal relationship amongst variables. Path analysis and structural equation modelling require the researchers to build up their models carefully by explicitly formulating the causal relationships amongst the outcomes, exposures and confounders. Path diagrams used by many SEM software packages as the means for model building are a very useful tool for causal thinking. In this chapter, we will use a few examples to illustrate how to develop statistical models within the framework of SEM and how to test causal relationships amongst variables within those models.
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Tu, YK. (2012). Directed Acyclic Graphs and Structural Equation Modelling. In: Tu, YK., Greenwood, D. (eds) Modern Methods for Epidemiology. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-3024-3_11
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DOI: https://doi.org/10.1007/978-94-007-3024-3_11
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