Regularization in Bifactor-(S-1)-Models

doi:None

Title	Authors

Home

This simulation study examined the performance of ridge and lasso regularization within a Bifactor-(S-1)-Model by varying sample size, the amount of non-informative covariates, the overall R² of the regularized regression as well as the amount of multicollinearity among predictors. For replicating the results obtained with the lslx-package (Huang et al. 2020), use the supplied materials for data generation, model estimation and model analysis. For replicating the result obtained by the StructuralEquationsModel.jl-package (Ernst & Peikert, 2022) please refer to the following repository: https://github.com/aaronpeikert/ridge-sem-convergence

OSF does not support the use of Internet Explorer. For optimal performance, please switch to another browser.

This website relies on cookies to help provide a better user experience. By clicking Accept or continuing to use the site, you agree. For more information, see our Privacy Policy and information on cookie use.

Start managing your projects on the OSF today.

Free and easy to use, the Open Science Framework supports the entire research lifecycle: planning, execution, reporting, archiving, and discovery.

Create an Account Learn More Hide this message

Main content

Home

Menu

Start managing your projects on the OSF today.

Main content

Links to this project

Home

Menu

Add new wiki page

Page permissions have changed

Wiki page deleted

Connected to the collaborative wiki

Connecting to the collaborative wiki

Collaborative wiki is unavailable

Browser unsupported

Start managing your projects on the OSF today.