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st: RE: RE: RE: Delete missing


From   "Lachenbruch, Peter" <Peter.Lachenbruch@oregonstate.edu>
To   "'statalist@hsphsun2.harvard.edu'" <statalist@hsphsun2.harvard.edu>
Subject   st: RE: RE: RE: Delete missing
Date   Mon, 10 May 2010 09:09:05 -0700

I agree with Nick - if a variable has absolutely nothing in it as the case for a missing column, it's really not usable at all and dropping it isn't really dropping a variable, it's just being sensible.  If you want to drop a variable because one or two (or more) observations are missing, that's a bad idea as I said.  In addition, for regulatory work, this idea could be legally problematic - a regulator could accuse the sponsor of shaping the data set to prove a point.

Tony

Peter A. Lachenbruch
Department of Public Health
Oregon State University
Corvallis, OR 97330
Phone: 541-737-3832
FAX: 541-737-4001


-----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Nick Cox
Sent: Sunday, May 09, 2010 10:51 AM
To: statalist@hsphsun2.harvard.edu
Subject: st: RE: RE: Delete missing

Tony's comment seems a bit more severe than the facts warrant. 

If you have missings Stata will just ignore them, so -drop-ping them
from the dataset is not going to make much difference to that. 

My impression as its author is that many of the uses of -dropmiss- (SJ)
in particular and many of the reasons for this request arise from
innocuous missings. For example, spreadsheet people often leave blank
rows and/or columns in their worksheets just as ways of making their
data more readable. Import into Stata will usually take such rows and
columns literally but they have no content and are best -drop-ped
straight away. There is no statistical issue in those situations raised
by -drop-ping missings, as the missings do not correspond to potential
data even in principle.   

Where it gets more complicated is that some people are tempted to -drop-
variables and/or observations in which _any_ values are missing. That's
usually going to lead to loss of information. That may be Tony's main
point. 

Nick 
n.j.cox@durham.ac.uk 

Lachenbruch, Peter

Generally, this is a very bad idea.  You will get biased estimates of
any parameters you estimate unless the data is missing at random.  Check
the multiple imputation manual.  Also note that Stata is not capitalized
as you have done.

Patricia Yu [pyu1@wisc.edu]

I have a question about deleting missing data.
I would like to delete cases if they have missing values in any
variables in
my dataset.
How can I do in STATA to delete these cases with any missing data?
Could you please share STATA codes with me?


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