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Re: st: permutations


From   David Airey <david.airey@vanderbilt.edu>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: permutations
Date   Mon, 17 Mar 2008 08:53:10 -0500

.

I calculated a test of a difference between any two SNP genotypes. You are saying you want to know which pairwise comparisons are different. If you just want those two probabilities (genotype 2 = genotype 0, genotype 1 = genotype 0), you get these by adding a couple lines to our code, and modifying the permute command as below. To get the other comparison (genotype 2 = genotype 1), you would need to use a different base comparison, or you would need to use the command lincom.

***do_begin***

describe
table age caco snp

program plogistic, rclass
version 10
args caco snp age
xi: logistic `caco' i.`snp' i.`age'
test _Isnp_1 _Isnp_2
return scalar chi2 = r(chi2)
test _Isnp_1
return scalar chi2_1 = r(chi2)
test _Isnp_2
return scalar chi2_2 = r(chi2)
end

set seed 3132008

permute caco chi2=r(chi2) chi2_1=r(chi2_1) chi2_2=r(chi2_2), ///
reps(1000): plogistic caco snp age

***do_end***


Monte Carlo permutation results Number of obs = 2394

command: plogistic caco snp age
chi2: r(chi2)
chi2_1: r(chi2_1)
chi2_2: r(chi2_2)
permute var: caco

------------------------------------------------------------------------------
T | T(obs) c n p=c/n SE(p) [95% Conf. Interval]
------------- +----------------------------------------------------------------
chi2 | .1560796 920 1000 0.9200 0.0086 . 9014202 .936058
chi2_1 | .1184664 724 1000 0.7240 0.0141 . 6951618 .7515127
chi2_2 | .1448991 719 1000 0.7190 0.0142 . 690024 .7466803
------------------------------------------------------------------------------
Note: confidence intervals are with respect to p=c/n.
Note: c = #{|T| >= |T(obs)|}

.


On Mar 17, 2008, at 5:23 AM, Christopher Intemann wrote:


Hello David,
thank you for the example, it was very helpful.
However, still the result is not what I'm actually up to.
In your example, you're calculating:
xi: logistic caco i.snp i.age
i.snp _Isnp_0-2 (naturally coded; _Isnp_0 omitted)
i.age _Iage_35-60 (naturally coded; _Iage_35 omitted)

Logistic regression Number of obs = 2116
LR chi2(7) = 21.17
Prob > chi2 = 0.0035
Log likelihood = -1455.9021 Pseudo R2 = 0.0072

------------------------------------------------------------------------------
caco | Odds Ratio Std. Err. z P>|z| [95% Conf. Interval]
------------- +----------------------------------------------------------------
_Isnp_1 | .9580097 .1193996 -0.34 0.731 .7503816 1.223088
_Isnp_2 | .9524632 .1218649 -0.38 0.703 .7412068 1.223931
_Iage_40 | 1.63372 .2251451 3.56 0.000 1.247017 2.14034
_Iage_45 | 1.545441 .216941 3.10 0.002 1.173722 2.034885
_Iage_50 | 1.634428 .2582141 3.11 0.002 1.199194 2.227627
_Iage_55 | 1.09121 .184666 0.52 0.606 .7831755 1.520399
_Iage_60 | 1.202247 .1956237 1.13 0.258 .8739581 1.653854
------------------------------------------------------------------------------

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