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The Causal Effects for a Causal Loglinear Model (1508.02985v1)

Published 12 Aug 2015 in stat.ME and stat.AP

Abstract: The analysis of the causality is important in many fields of research. I propose a causal theory to obtain the causal effects in a causal loglinear model. It calculates them using the odds ratio and Pearl's causal theory. The effects are calculated distinguishing between a simple mediation model (model without the multiplicative interaction effect) and a mediation model with the multiplicative interaction effect. In both models it is possible also to analyze the cell effect, which is a new interaction effect. Then in a causal loglinear model there are three interaction effects: multiplicative interaction effect, additive interaction effect and cell effect

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