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Re: st: Randomly picking observations based on a certain condition


From   Nikhil Srivastava <[email protected]>
To   [email protected]
Subject   Re: st: Randomly picking observations based on a certain condition
Date   Fri, 15 Apr 2011 15:52:32 -0700

This works!Thanks a lot for the help.

Nikhil

On Wed, Apr 13, 2011 at 3:16 PM, Andrew Dyck <[email protected]> wrote:
> After you consider the comments from Nick and J, you wish to proceed
> with your analysis as you initially stated it, I think the following
> should work. Here I create some sample data with 50 observations and 5
> groups (quintiles). See if this might work for your data the way I
> understood your question. I use the cutoff of 10 adults instead of 100
> to keep the dataset small.
>
> * sample data
> set obs 50
> egen group = seq(), from(1) to(5)
> gen adults = round( runiform()*5, 2 )
>
> * random variable for sorting
> gen r = runiform()
>
> * create a cumulative sum of adults
> * sorting randomly within the group.
> bysort group (r): gen cumul_adults = adults[1]
> bysort group : replace cumul_adults = adults[_n] + cumul_adults[_n-1] if _n > 1
> drop r
>
> * keep all obs below the cutoff
> keep if cumul_adults <= 10
>
> Good luck,
> Andrew
>
>
> On Wed, Apr 13, 2011 at 2:02 PM, Nikhil Srivastava
> <[email protected]> wrote:
>>
>> I am not trying to actually sample households. As I wrote in my rely
>> to Nick,I am trying look at the effectiveness of a transfer program
>> targeted to adults of a household which has a certain exclusion error.
>> The exclusion error that we are assuming is that 1 percent of eligible
>> participants within each expenditure quintile do not receive the
>> benefits. In my sample within the first quintile 1 percent of the
>> total adults comes to around 100. Thus for the first quintile I need
>> to randomly assign non-beneficiary status to households so that the
>> total number of adults for these households comes to 100. Similarly I
>> have to pick randomly 1 percent of adults for each quintile and assign
>> them non-beneficiary status. In my previous mail I used the number 100
>> as an example. Thanks
>>
>> Nikhil
>>
>> On Wed, Apr 13, 2011 at 1:06 PM, Joerg Luedicke
>> <[email protected]> wrote:
>> > On Wed, Apr 13, 2011 at 3:17 PM, Nikhil Srivastava
>> > <[email protected]> wrote:
>> >> Hi,
>> >>
>> >> I have a dataset at the household level which contains the expenditure
>> >> details of a sample of households. The dataset also records the number
>> >> of adults within each household. I have divided this dataset into 5
>> >> quintiles based on the level of expenditure. Now I need to randomly
>> >> select a set of observations within each quintile so that the sum of
>> >> the adults for those observations comes to 100. Could somebody please
>> >> help me in writing a code for this part?
>> >>
>> >> I would really appreciate any help in this regard. Thanks
>> >
>> > Do I understand that right, you want to sample households, and within
>> > each quintile of household expenditure, the number of household
>> > members among sampled households is supposed to add up to 100? Why
>> > would you do that? Why not just taking a random sample of households
>> > or a stratified sample with respect to household size, if that is a
>> > concern. That way, you would at least have a clear picture of the
>> > population you are targeting, whereas in the other case, this picture
>> > becomes pretty blurry, no?
>> >
>> > J.
>> > *
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>> >
>>
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>
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