Hello, I need to test the significance of the increase in R2 of two nested models in SEMPLS and I am using the following formula:
F=((R2LR2S)/(dfLdfS))/((1R2L)/(NdfL1))
where R2L is the Rsquared of the endogenous variable from the model with more variables, and R2S is the Rsquared of the predicted variable from the model with fewer variables. The quantity dfLdfS is the difference in the number of variables between the two models. N is the sample size.
However, my problem is what should I consider as variables in my model for the comparison? The indicators of the latent variables or the Latent variables themselves? It would make a huge difference as any latent constructs has 10 indicators. Meanwhile, I have just 4 Latent constructs in the smaller model and 6 in the bigger one. So if I consider indicators I have 6040 as a difference of variables in the two models. However, if I consider latent constructs I have 64. And this, of course, will affect also the degrees of freedom.
Significant increase in R^2 in 2 nested models through Ftest

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 Real name and title: Dr. Eleonora Nicolosi

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Re: Significant increase in R^2 in 2 nested models through Ftest
I have the same problem! Did you sort it out at the end?
I assume that we should consider the number of latent variables for the calculation but I am not sure either! Could not find any clear explanation on published papers!
I assume that we should consider the number of latent variables for the calculation but I am not sure either! Could not find any clear explanation on published papers!