r2ₘlm: A command for computing R-squared measures for models fit by mixed

View Full Paper

Ask AI

Bookmark

Authors

Discussion

This article demonstrates how r2_mlm computes R-squared measures in mixed models, suggesting improved accuracy in multilevel modeling.

Results show the R-squared measures can clarify model effectiveness and potential bias.
Key features include alerts for potential conflation bias in model specifications.
The method involves a new postestimation command for multilevel models and mixed models.
Overall, this framework may enhance the interpretability of statistical models in research.

Gambino et al. (2025) studied this question.

View Full Paper

Ask AI

Bookmark

View Full Paper

Ask AI

Bookmark

Authors

This article demonstrates how r2_mlm computes R-squared measures in mixed models, suggesting improved accuracy in multilevel modeling.

Results show the R-squared measures can clarify model effectiveness and potential bias.
Key features include alerts for potential conflation bias in model specifications.
The method involves a new postestimation command for multilevel models and mixed models.
Overall, this framework may enhance the interpretability of statistical models in research.

Gambino et al. (2025) studied this question.

View Full Paper

Ask AI

Bookmark