323
Views
0
CrossRef citations to date
0
Altmetric
Research Articles

Regularized 2SLS Estimation of Structural Equation Model Parameters

Pages 920-932 | Received 31 Jan 2022, Accepted 19 Apr 2022, Published online: 17 Jun 2022
 

Abstract

There is a growing interest among methodological and applied researchers in extending the use of regularization techniques (e.g., lasso regression, the elastic net) to structural equation models (SEMs). To date, most of the extensions have been based on combining the respective penalty function with the standard Maximum Likelihood fit function for SEMs. In the present article, we describe two ways in which the Two-Stage Least Squares (2SLS) estimator, an equation-by-equation estimator of SEMs, can be combined with these regularization techniques. Both approaches can be used to regularize the parameters in single equations (“local” regularization), and for both approaches, the parameters can be determined very quickly and efficiently using standard software. We evaluated the two methods in two simulation studies. We were able to show that both approaches provide suitable parameter estimates and can be used to select factor models and path coefficients even when the model is incorrectly specified.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 53.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 412.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.