Hi ,
I have to compare the following (nested/ hierarchical?) models in
order to test whether the variables included in second model
significantly increase the goodness of fit.
1) Y = α0 + α1 BV + α2NI + ε
2) Y = ß0 + ß1 BV + ß2 NI + ß3 TANG + ε
My questions are the following:
I. It's not clear to me the difference between nested and hierarchical
regressions. Is defined hierarchical a regression in which I simply
add new variables ? If it so, my models (1-2) should be hierarchical.
Conversely, is nested model a regression in which I decompose the
components of a variable? For example, if I add a third model, in
which TANG is decomposed in TANG1 TANG2 TANG3.
3) Y = g0 + g1 BV + g2 NI + g3 TANG1+ g4 TANG2+ g5TANG3+ ε
II. In order to test whether the goodness of fit of 2 model
significantly increases, I employ the following test, found in
econometric textbook (considering model 2 = full model):
Δ R2/ Δdf = F (Δ R2 , df full)
(1- R2full)/df full
Is it correct ?? Can you give me some specific reference on this test ?
III. In Cox's book "A gentle introduction to Stata" page 216, test of
semipartial correlation of variables is performed by pcorr2. Even if
the author suggests to install it with findit pcorr2, I am not able to
find the program anywhere. Can anybody suggest how can I install it
???
Thanks so much.
Kind Regards,
Serena
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