Re: st: re: Sample with weights

[Nick Winter <nw53@cornell.edu>]

Doesn't work.

First, you need to sort the other direction.

But more seriously, this does not generate selection probabilities 
proportional to size.  Consider this code, which creates fake data, 
then draws 500 samples of 200 using this methed.  The graph at the 
end makes clear that the selection probabilities are not proportional to size:

clear
set obs 1000
gen firm = _n
set seed 12345678
gen size = int(uniform()*100) + 1
gen sampled = 0

forval i=1/500 {
        gen ppsorder = uniform() * size
        gsort -ppsorder
        qui replace sampled = sampled+1 if _n <= 200
        drop ppsorder
}

graph twoway scatter sampled size

--Nick WInter



At 11:04 AM 10/1/2005, you wrote:

> This is simple, produces a sample of exactly the desired size,
> and I believe fulfills the condition of the probability of selection
> being proportional to size .
> *Assume "Size" is the company size variable, and M is the desired sample size
> gen ppsorder = uniform() * Size
> sort ppsorder
> keep if _n <= M
> drop ppsorder
>
> Yes, sorting the file is a bit clumsy, but this is presumably a one 
> time thing,
> not something appearing inside a loop.
>
> Regards,
>
>
> =-=-=-=-=-=-=-=-=-=-=-=-=
> Mike Lacy
> Fort Collins CO USA
> (970) 491-6721 office
________________________________________________________
Nicholas J. G. Winter                     607.255.8819 t
Assistant Professor                       607.255.4530 f
Department of Government              nw53@cornell.edu e
Cornell University        falcon.arts.cornell.edu/nw53 w
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Ithaca, NY 14853-4601 

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