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st: RE: Generating random samples, with replacement

From   "David Harrison" <>
To   <>
Subject   st: RE: Generating random samples, with replacement
Date   Fri, 25 Feb 2005 15:28:06 -0000

To just draw a single bootstrap sample, the command is -bsample-. I find the -weight()- option to -bsample- can be a very useful thing to speed up these procedures - this stores the bootstrap sample using frequency weights rather than replacing the data in memory, e.g.

gen bsw=.
forvalues i=1/10 {
	bsample, weight(bsw)
	logistic y x1 x2 [fw=bsw]


-----Original Message-----
From: Elaine Thomas []
Sent: 25 February 2005 15:12
Subject: st: Generating random samples, with replacement

I am trying to write a routine to apply a step-wise logistic modelling 
procedure to a number of samples from a core data set. I want the 
samples to be the same size as the original and be sampled with 
replacement. I know that bs and bstrap will perform bootstrapping on the 
coefficients of a standard logistic model, but I want to perform a 
step-wise procedure within each sample, rather than pre-define the 
model. How can I get Stata to produce, say, 200 random samples from my 
original data that I can then call on in a later program?

So far I have worked out how to reproduce a standard logistic model 
(logistic y x1 x2) and take the coefficients and then using forvalues 
(with dummy data) to move through my samples of data (bs1.dta, bs2.dta 
etc), each time adding the coefficients (_b[x1] _b[x2]) to a new 
datafile (t) as below

    postfile `sort' x1 x2 using t, replace
    forvalues i = 1(1) `n'{
    use bs`i'.dta
    logistic y x1 x2
    post `sort' (exp(_b[x1])) (exp(_b[x2]))

I am building this process up as I dont do much programming. What i 
really want to do next is to generate the random samples within this 
loop, rather than having to have the datasets already formed and call on 
them. So I dont want not to use bstrap to bootstrap the coefficients, I 
want to be able to get it (or something akin to it) to generate random 
samples for me.

Any help, even knowing how to generate random samples, with replacement, 
that I can store as separate datasets would be helpful

Dr Elaine Thomas
Lecturer in Biostatistics
Primary Care Sciences Research Centre
Keele University
North Staffordshire

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