By Nancy Abramson | 06/17/19

Structural equation modeling (SEM) is a powerful and flexible toolbox for statistical inference – the practice of forming judgments typically on the basis of random sampling. SEM is a set of mathematical models, computer algorithms and statistical methods that function as tools to help with statistical inference. However, despite the flexibility of structural equation models (SEMs), there are few efficient and effective inference methods that can work with the kinds of problems with many variables and possible values that commonly occur in contemporary fields, such as genomics.

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