Quote:
Originally Posted by barneyg
What are the correlations between those variables? I'd assume Xp is strongly correlated with them if it becomes the least significant variable once the others are included. That said, with 30 data points any tstat above ~2 will be significant and the tstatistic on Bp seems to be 1.5*5.5 = 8.25 (square root of 30 = 5.5).
I'm not an econometrician (I don't play one on TV either), but I know that Rsquare doesn't mean squat when no intercept is included in the model. Was there one in yours?
I have seen a measure such as 'incremental Rsquare' i.e. (newold)/old where 'new' is the R2 from the full model and 'old' is the one with only an intercept or something.
In models with stable time series, people often calculate first differences i.e. Y'(1985) = Y(1985)  Y(1984) and run the model on those changes instead of the level. It changes the narrative because 'last year' is the benchmark for each observation but since your objective is often 'what makes Y change' it works. There's a deeper econometric(al?) reason that justifies first differences as well.
I'll try to find time to look at the other thread too.

This is not an argument. This is assuming that your methodology is true. No one is questioning your math. Its your thinking that drives you to use proven wrong math technique to analyze human performance and predict past or future performance.