Hi,
I have couple of questions on Fracpol, I tried finding answers through
help and the internet but was unsuccessful. The results of my model are
posted below.
1) How acceptable is the use of fractional polynomial in the
literature. Is it considered data mining?
2) What is the structure of the best relation?
Is it: y=b0 + b1 X^-.5 + X^-.5*ln(X) ?
3) Why is X = (dist+2.860107421875)/1000)? why the addition of 2.8
and division by 1000?
4) What is the exact meaning of deviance? Is lower (more negative)
better or worst?
. fracpoly reg b dist, adjust (no) compare
........
-> gen double Idist__1 = X^-.5 if e(sample)
-> gen double Idist__2 = X^-.5*ln(X) if e(sample)
(where: X = (dist+2.860107421875)/1000)
Source | SS df MS Number of obs = 57
-------------+------------------------------ F( 2, 54) = 3.45
Model | .014450698 2 .007225349 Prob > F = 0.0390
Residual | .113204826 54 .002096386 R-squared = 0.1132
-------------+------------------------------ Adj R-squared = 0.0804
Total | .127655524 56 .002279563 Root MSE = .04579
------------------------------------------------------------------------------
y | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
Idist__1 | .04901 .0190668 2.57 0.013 .0107834 .0872366
Idist__2 | .007933 .0031175 2.54 0.014 .0016829 .0141832
_cons | -.0443816 .0171458 -2.59 0.012 -.0787569 -.0100063
------------------------------------------------------------------------------
Deviance: -192.87. Best powers of distance among 44 models fit: -.5 -.5.
Fractional polynomial model comparisons:
------------------------------------------------------------------------------
dist df Deviance Res. SD Dev. dif. P [*] Powers
------------------------------------------------------------------------------
Not in model 0 -186.025 .047745 6.848 0.174
Linear 1 -188.380 .047192 4.492 0.247 1
m = 1 2 -189.268 .046825 3.604 0.193 .5
m = 2 4 -192.873 .045786 -- -- -.5 -.5
------------------------------------------------------------------------------
[*] P-value from deviance difference comparing reported model with m = 2 model
Many thanks for your help
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