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Re: st: Missing observations


From   njcoxstata@gmail.com
To   "statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu>
Subject   Re: st: Missing observations
Date   Thu, 20 Jun 2013 18:29:32 +0100

This is really isn't clear to me, but it may be that -var1- and -var2- should be stacked on top of each other.

Nick
njcoxstata@gmail.com

On 20 Jun 2013, at 15:41, Csaba <csaba.kertai@hotmail.co.uk> wrote:

> Nick,
> 
> Thank you for your reply. Yes you are right I muddled up observations with values. I meant to write values not observations. My problem is that if I use 'drop if missing(var2)' that will drop values for each variable in my data set. 
> 
> I need to compare the means/medians of 2 variables. Var1 has 1125 non-missing values, var2 has 169 non-missing values. I might be doing sth wrong but when I try using bootstrapping I get a message saying that I should drop any missing values as bootstrapping cannot distinguish between missing and non-missing values. That's why I want to drop missing values for Var2. Basically, I want to achieve the same result as with the unpaired two-sample mean comparison test but with bootstrapping. 
> 
> Thanks a lot!
> 
> On 20 Jun 2013, at 12:32, Nick Cox <njcoxstata@gmail.com> wrote:
> 
>> -drop- as used here drops entire observations (outside Stata
>> observations are known as rows, cases, records). You seem to be under
>> the impression that there is an operation
>> 
>> drop missing values
>> 
>> that is somehow different from
>> 
>> -drop- observations
>> 
>> but I don't know what that would look like.
>> 
>> In your example if -var2- has only 169 non-missing values (_not_
>> observations) then
>> 
>> drop if missing(var2)
>> 
>> will leave precisely 169 observations. I don't understand how that is
>> a surprise or what else you want.
>> 
>> Nick
>> njcoxstata@gmail.com
>> 
>> 
>> On 20 June 2013 11:17, Csaba Kertai <csaba.kertai@hotmail.co.uk> wrote:
>> 
>>> I need a bit of help with dropping missing observations. If I use 'drop if missing(var)' or drop if 'var'==. etc. many other observations are dropped as well. More precisely, var1 has 1125 observations and var2 has 169 observations. I want to drop missing observations for var2 but if I use drop if var2==. then this will keep only 169 observations for each variable. I only want to drop values that are missing.
>> 
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