On Non-Regularized Estimation of Psychological Networks

Donald Williams, Mijke Rhemtulla, Anna Wysocki & Philippe Rast
An important goal for psychological science is developing methods to characterize relationships between variables. The customary approach uses structural equation models to connect latent factors to a number of observed measurements. More recently, regularized partial correlation networks have been proposed as an alternative approach for characterizing relationships among variables through covariances in the precision matrix. While the graphical lasso (glasso) method has merged as the default network estimation method, it was optimized in fields outside...
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