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Structural Equation Model Trees

Recursive Partitioning with Structural Equation Models in R

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semtree

Recursive Partitioning with Structural Equation Model Trees

Structural Equation Model Trees (SEM Trees) combine the strengths of Structural Equation Models and decision trees by building tree structures that separate a dataset recursively
into subsets with significantly different parameter estimates in a
SEM. This approach provides a data-driven but theory-constrained search in model space.

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References

Brandmaier, A. M., Oertzen, T. v., McArdle, J. J., & Lindenberger, U. (2013). Structural equation model trees. Psychological Methods, 18, 71-86. doi: 10.1037/a0030001

Brandmaier, A. M., Oertzen, T. v., McArdle, J., & Lindenberger, U. (in press). Exploratory data mining with structural equation model trees. In J. J. McArdle & G. Ritschard (Eds.), Contemporary issues in exploratory data mining in the behavioral sciences. New York: Routledge.

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http://www.r-project.org/

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http://openmx.psyc.virginia.edu/

Get Onyx:
http://onyx.brandmaier.de

About

semtree is a freely available package for the statistical computing language R. It is based on the modeling package OpenMx. semtree provides model-based recursive partitioning for Structural Equation Models.

Please note: semtree is not related to
  • SEM-tree: Sequence Embedding Multiset tree
  • SemTree: Ontology-Based Decision Tree Algorithm for Recommender Systems
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