st: Re: Construct Null Datasets through Bootstrap Resampling

["Michael Blasnik" <michael.blasnik@verizon.net>]

It seems like you want something similar to -permute- except you want to 
permute all of the variables, not just one.  Here's a short program that 
will scramble all of the variables in your dataset.  You can usel this 
within your own program and perform a monte carlo simulation (check 
out -simulate-).

program define scramble
version 9.2
syntax [varlist]
tempvar hold order rand
gen long `order'=_n
foreach var of local varlist {
gen `rand'=uniform()
gen `hold'=`var'
sort `rand'
replace `var'=`hold'[`order']
drop `rand' `hold'
}
end

Michael Blasnik


----- Original Message ----- 
From: "Erik Ingelsson" <Erik.Ingelsson@pubcare.uu.se>
To: <statalist@hsphsun2.harvard.edu>
Sent: Thursday, November 30, 2006 1:31 PM
Subject: st: Construct Null Datasets through Bootstrap Resampling



> Dear Statalist users,
>
> I am trying to construct null data sets through bootstrap resampling,  to 
> be able to account for multiple testing in genetic analyses. I  would like 
> to sample my genotypes and phenotypes randomly with  replacement (without 
> keeping linked them together as the original  observations in my dataset), 
> and then run regressions on these samples  to evaluate a distribution of 
> minimum probability values. Thereby, I  will obtain empirical p-values by 
> comparing the nominal p-values with  the distribution of probability from 
> the null data sets. I have seen  this implemented in SAS, but I hope that 
> it could be done also in STATA.
>
> In my ?trail-and-error? approach, I have come so far, that I have  learned 
> how to use bootstrap sampling to get a new dataset with  p-values from a 
> set of regressions. However, these simulations are  still using my 
> original observations (although creating new samples),  while I would like 
> the observations to be randomly created from the  available variables (not 
> keeping them together as in the original  dataset). Below is the code for 
> what I have done so far. Variables  linj001-linj004 are the genotypes, 
> thus the important independent  variables; the other variables are 
> covariates to adjust for; stset and  all definitions, etc are done above. 
> In reality, I will have much more  regressions to include in the 
> simulation, but this is just for  learning how to do it.
>
> ---
> *Program with the commands to be run in all bootstrap samples*
> capture program drop myboot
> program myboot, rclass
>      stcox linj001 whoht70 adadiab70 ami70 vit70 z972 z290 z085 zekg_lvh
>      return scalar p1 = 2*(1-normal(abs(b[linj001]/_se[linj001])))
>      stcox linj002 whoht70 adadiab70 ami70 vit70 z972 z290 z085 zekg_lvh
>      return scalar p2 = 2*(1-normal(abs(b[linj002]/_se[linj002])))
>      stcox linj003 whoht70 adadiab70 ami70 vit70 z972 z290 z085 zekg_lvh
>      return scalar p3 = 2*(1-normal(abs(b[linj003]/_se[linj003])))
>      stcox linj004 whoht70 adadiab70 ami70 vit70 z972 z290 z085 zekg_lvh
>      return scalar p4 = 2*(1-normal(abs(b[linj004]/_se[linj004])))
> end
>
> *Run the program in the original sample*
> myboot
> ret list
>
> *Bootstrapping in 10000 samples*
> bootstrap "myboot" p1=r(p1) p2=r(p2) p3=r(p3) p4=r(p4), reps(10000) 
> saving(C:\bootstrapsample) replace
> ---
>
> This leaves me with a dataset (C:\bootstrapsample) which consists of  the 
> p-values from the 4 regressions derived from 10000 simulations.  However, 
> this is not exactly what I need, since the variables are  still 
> ?connected? in the original observations (and then randomly  chosen for my 
> simulated sets). I would like to get simulations with  all variables 
> scrambled, so that new observations with all variables  scrambled are 
> created in a number of bootstrap simulations, and then  used for 
> regressions. The present macro can give me 10000 simulated  p-values for 
> the regressions, based on samples with replacement, but  these simulations 
> are reusing the actual 2000 observations from the  original dataset. Now I 
> would like to create a ?null dataset?, in  which I instead of sampling 
> from the observations in the real dataset,  I would like Stata to randomly 
> ?make up? observations from the  existing variables and values, so that I 
> have 2000 fake observations  (with random selection of all variables) to 
> base the regressions on,  in 10000 simulations.
>
> I have read the help files, manual, Statalist, searched at Internet,  even 
> asked Technical Support (which helped me to come this far, but  not the 
> last part). I am using Stata 8.2 for Windows. Is there a way  to do this? 
> Did I explain what I want to do properly? Is there anyone  who can help me 
> with this?
>
> Thanks a lot in advance,
> Erik Ingelsson
>
>
> ---
> Erik Ingelsson, MD, PhD
>
> Current affiliation (until June 30, 2007):
> Framingham Heart Study
> 73 Mt. Wayte Avenue, Suite 2
> Framingham, MA 01702-5827
> Phone: 508-935-3453
> Fax: 508-626-1262
> Cell: 508-202-8493
>
> Permanent affiliation:
> Uppsala University, Department of Public Health and Caring Sciences, 
> Uppsala
> Science Park, SE-751 85 Uppsala, SWEDEN.
> Fax: +46-18-611 79 76
> E-mail: erik.ingelsson@pubcare.uu.se
> ---
>
>
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