1994 | OriginalPaper | Chapter
Inferring causal structure among unmeasured variables
Author : Richard Scheines
Published in: Selecting Models from Data
Publisher: Springer New York
Included in: Professional Book Archive
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Linear structural equation models with latent variables are common in psychology, econometrics, sociology, and political science. Such models have two parts, a measurement model that specifies how the latent variables are measured, and a structural model which specifies the causal relations among the latent variables. In this paper I discuss search procedures for finding a ‘pure’ measurement model and for using this pure model to determine features of the structural model. The procedures are implemented as the Purify and MIMbuild modules of the TETRAD II program.