Statistical analysis uses data to draw conclusions about phenomena, however, the causal inference has a different logical approach, it begins with a premise or theory and then try to deduce whether it fits the data. Here I'm using SEM models, establishing the relationship of cause and effect with a covariance matrix to eliminate all alternative causes.