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<https://discovery.ucl.ac.uk/id/eprint/10059558> <http://purl.org/ontology/bibo/abstract> "The identification of causal relationships between random variables from large-scale\r\nobservational data using directed acyclic graphs (DAG) is highly challenging. We\r\npropose a new mixed-effects structural equation model (mSEM) framework to estimate\r\nsubject-specific DAGs, where we represent joint distribution of random variables in the\r\nDAG as a set of structural causal equations with mixed effects. The directed edges\r\nbetween nodes depend on observed exogenous covariates on each of the individual\r\nand unobserved latent variables. The strength of the connection is decomposed into\r\na fixed-effect term representing the average causal effect given the covariates and a\r\nrandom effect term representing the latent causal effect due to unobserved pathways.\r\nThe advantage of such decomposition is to capture essential asymmetric structural\r\ninformation and heterogeneity between DAGs in order to allow for the identification\r\nof causal structure with observational data. In addition, by pooling information across\r\nsubject-specific DAGs, we can identify causal structure with a high probability and\r\nestimate subject-specific networks with a high precision. We propose a penalized\r\nlikelihood-based approach to handle multi-dimensionality of the DAG model. We propose\r\na fast, iterative computational algorithm, DAG-MM, to estimate parameters in mSEM and\r\nachieve desirable sparsity by hard-thresholding the edges. We theoretically prove the\r\nidentifiability of mSEM. Using simulations and an application to protein signaling data,\r\nwe show substantially improved performances when compared to existing methods and\r\nconsistent results with a network estimated from interventional data. Lastly, we identify\r\ngray matter atrophy networks in regions of brain from patients with Huntington’s disease\r\nand corroborate our findings using white matter connectivity data collected from an\r\nindependent study."^^<http://www.w3.org/2001/XMLSchema#string> .
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