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From |
Stas Kolenikov <skolenik@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: proportional random sampling |

Date |
Tue, 25 Oct 2011 12:36:08 -0500 |

It looks like sample 27, by( ecs ) would likely achieve what you need (where 27% = 12/44). Define "elegant" first so that we know what you are looking for :). If you want an absolutely full control over what's going on, you can do this: set seed 20111025 tempvar r sample generate `r' = uniform() generate byte `sample' = 1 bysort ecs (`r') : replace `sample' = 0 if _n > 8 & ecs == "larger group" bysort ecs (`r') : replace `sample' = 0 if _n > 4 & ecs == "smaller group" count if `sample' assert r(N) == 12 keep if `sample' drop `r' `sample' On Tue, Oct 25, 2011 at 12:05 PM, Steve Nakoneshny <scnakone@ucalgary.ca> wrote: > Hi Cam, > > We're investigating in a retrospective study whether or not a particular pathologic feature of a tumour can be accurately predicted using an imaging modality (CT scan) prior to surgery. We've identified 44 eligible patients for which the distribution of this feature is approximately 2:1. Prior to undertaking the majority of the work, it was suggested that we take a random sample of each group (positive and negative) and ask the radiologists to asses their scans blindly in order to validate the data collection instrument as a pilot test. > > The plan was to go with 5 from each arm, but it was later suggested that we provide them with an unequal distribution so that the radiologists don't automatically assume a 50/50 split. I could easily go with a fully randomized selection, but I want to ensure that we have a representative proportion for each, hence wanting to retain the 2:1 ratio. > > I have already narrowed down the dataset to a random sample I'm comfortable with via the code I employed previously. I was simply asking of the list if anyone could suggest an alternate means of arriving at a similar result in perhaps a more elegant fashion as a purely intellectual exercise. If not, that's fine too. > > Thanks, > Steve > > On 2011-10-24, at 8:51 PM, Cameron McIntosh wrote: > >> Steve, >> I think that if you described the motivation for this exercise, it might help elicit advice -- perhaps some that even suggests an alternative way of looking at your problem, whatever that may be. :) >> Thanks, >> Cam >> >> ---------------------------------------- >>> From: scnakone@ucalgary.ca >>> To: statalist@hsphsun2.harvard.edu >>> Date: Mon, 24 Oct 2011 17:15:20 -0600 >>> Subject: st: proportional random sampling >>> >>> Dear Statalisters, >>> >>> I have a small dataset (n=44) from which I want to draw a random sample of records. The distribution of these records across my variable of interest in approximately 2:1. What I wish to do is to create a random sample of records of size n that retains the proportional distribution across my variable of interest. >>> >>> Assuming a random sample where n=12, I wrote the following code: >>> >>> sort ecs >>> by ecs: sample 8,count >>> sample 50 if ecs==1 >>> >>> ------ >>> Although how I coded it certainly works, what I am wondering if there is a more elegant means of coding to achieve a similar result? >>> >>> >>> Thanks, >>> Steve >>> * >>> * For searches and help try: >>> * http://www.stata.com/help.cgi?search >>> * http://www.stata.com/support/statalist/faq >>> * http://www.ats.ucla.edu/stat/stata/ >> >> * >> * For searches and help try: >> * http://www.stata.com/help.cgi?search >> * http://www.stata.com/support/statalist/faq >> * http://www.ats.ucla.edu/stat/stata/ > > > * > * For searches and help try: > * http://www.stata.com/help.cgi?search > * http://www.stata.com/support/statalist/faq > * http://www.ats.ucla.edu/stat/stata/ > -- Stas Kolenikov, also found at http://stas.kolenikov.name Small print: I use this email account for mailing lists only. * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**Follow-Ups**:**Re: st: proportional random sampling***From:*Steve Nakoneshny <scnakone@ucalgary.ca>

**References**:**st: proportional random sampling***From:*Steve Nakoneshny <scnakone@ucalgary.ca>

**RE: st: proportional random sampling***From:*Cameron McIntosh <cnm100@hotmail.com>

**Re: st: proportional random sampling***From:*Steve Nakoneshny <scnakone@ucalgary.ca>

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