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st: interpreting multivariable fractional polynomials
From
"Casey P. Durand" <[email protected]>
To
[email protected]
Subject
st: interpreting multivariable fractional polynomials
Date
Thu, 13 May 2010 12:17:15 -0700
Hi folks,
I'm new to using multivariable fractional polynomials -mfp- in Stata,
and I have a question about interpretation of the dual coefficients
from a second degree FP . The best fitting model was a (-2, -2)
transformation, and this is my output from the logistic regression
using those transformations (street_1 & street_2):
Logistic regression Number of obs
= 364
LR
chi2(11) = 79.55
Prob >
chi2 = 0.0000
Log likelihood = -113.04482 Pseudo R2 = 0.2603
------------------------------------------------------------------------------
meets_rec | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
street_1 | 1.002819 .9828367 1.02 0.308 -.9235053 2.929144
street_2 | -15.11272 5.243973 -2.88 0.004 -25.39072 -4.834722
child_gend | -1.904081 .4017071 -4.74 0.000 -2.691413 -1.11675
|
child_ra |
2 | .0318764 1.010836 0.03 0.975 -1.949325 2.013078
3 | .136247 .4551104 0.30 0.765 -.7557529 1.028247
4 | .0477573 .7104908 0.07 0.946 -1.344779 1.440294
5 | -1.37826 .71353 -1.93 0.053 -2.776753 .0202333
6 | .4384325 .6696987 0.65 0.513 -.8741529 1.751018
|
free_lunc | .9778007 .3936116 2.48 0.013 .2063361 1.749265
child_age | -.8609912 .1538146 -5.60 0.000 -1.162462 -.5595202
preserve | -.6135725 .4557935 -1.35 0.178 -1.506911 .2797663
_cons | 12.0511 2.034686 5.92 0.000 8.063188 16.03901
------------------------------------------------------------------------------
Based on what I've seen in other published papers, it seems that I can
present the results graphically (i.e. predicted odds v. the
untransformed variable), and/or present odds ratios using hypothetical
values. My question is how to do the latter. Given the range of
possible answers on the continuous, untransformed "street" variable
(1-5), I'd like to give the OR predicted by the above coefficients
using a score of 1 as the referent category, while holding all other
variables at their mean, for the scores of 2,3,4 & 5. Though I've
read the help section and manual for -adjust- and -margins-, I can't
figure out how to get the predicted odds ratios and 95% CIs for these
hypothetical scores.
Thanks in advance for any help you can provide,
Casey
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