Causal Discovery and MIMIC Models

This thesis presents an alternative method for the detection of MIMIC models. Previous methods (such as factor analysis) suffer from a number of significant aws and limitations, which the new method (a causal search algorithm) doesn't suffer. A new algorithm is introduced, followed by a worked-through example of its application. Discussion focuses on some of the limiting assumptions the algorithm currently requires. Finally, recommendations for future work address improvements of the algorithm, as well as its applicability