Solved – A way to compute significance of R-squared change across models in a path model, or specifically lavaan

model comparisonpath-modelr-squaredregressionstructural-equation-modeling

I have a straightforward path model with a single endogenous variable and multiple observed predictors – in other words, a regression. (I'm doing it as a path model to be able to easily test mediation later). For now, I really need to know how to test for significance in R2 as I add predictors – the same as you get with the F-change statistic in OLS. If there's no straightforward way, is there perhaps a formula I could do by hand? Thanks in advance!

Best Answer

If I understand correctly, you would like to compare alternative SEM models. In this case, I believe that you have to use the scaled chi-square difference test statistic (with Satorra-Bentler correction): see and (the original paper) You can perform this test by using lavaan's function anova(), which automatically detects the presence of nested models and applies the correction.

For a non-nested models comparison, you could use either one of the following R packages: nonnest2 ( and simsem ( Both packages support lavaan classes' objects. For simsem, in addition to the documentation, you can take a look at non-nested models comparison examples here.

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