Hello,
Hope you are all well!
I have a problem and I really hope you can help me.
I would like to test if the difference in the R2 of two nested models is significant. For both models, I am using exactly the same data-set. In the second model, I just added an exogenous construct. Variables are not normally distributed.
I got Bias-Corrected accelerated confidence intervals for R2 values in both models through bootstrapping procedure (5000 samples). My questions are:
1. It is safe to say that if those confidence intervals do not overlap then the two R2 are different? Or should I account for the number of variables added before comparing the R2? how? Maybe I could use confidence intervals fro R2 adjusted?
2. Also, I was thinking to just get the differences of R2 for each sample produced through the bootstrap procedure. Then construct the Bias-corrected confidence interval on the distribution of those differences. Would that be ok?
3. If I need to compare R2 on more than two nested models should I build confidence intervals accounting for the Bonferroni correction?
Do you have any suggestions?
Thank you for reading the above!
E.
test difference between two R2 of nested models through the Bias corrected accelerated confidence intervals
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- PLS Junior User
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- Real name and title: Dr. Eleonora Nicolosi