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Re: st: RE: RE: sample size reduced significantly


From   "Yu Chen, PhD" <profyuchen@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: RE: RE: sample size reduced significantly
Date   Fri, 12 Apr 2013 11:19:12 -0500

Richard, thank you so much. I think -misstable- is very helpful!



On Thu, Apr 11, 2013 at 4:00 PM, Richard Goldstein
<richgold@ix.netcom.com> wrote:
> if you are interested in examining the pattern of missing values across
> your predictors, use the -misstable- command
>
> Rich
>
> On 4/11/13 4:51 PM, David Radwin wrote:
>> Yes, this is called listwise deletion. You also can count the number of
>> observations with one or covariates with missing values:
>>
>> . count if missing(var1, var2, var3, etc)
>>
>> or the number of observations with no missing values:
>>
>> . count if !missing(var1, var2, var3, etc)
>>
>> David
>> --
>> David Radwin
>> Senior Research Associate
>> MPR Associates, Inc.
>> 2150 Shattuck Ave., Suite 800
>> Berkeley, CA 94704
>> Phone: 510-849-4942
>> Fax: 510-849-0794
>>
>> www.mprinc.com
>>
>>
>>> -----Original Message-----
>>> From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-
>>> statalist@hsphsun2.harvard.edu] On Behalf Of Arya Eskamani
>>> Sent: Thursday, April 11, 2013 1:35 PM
>>> To: statalist@hsphsun2.harvard.edu
>>> Subject: st: RE: sample size reduced significantly
>>>
>>> In your explanatory variables, do you have any rows that with a missing
>>> field?  When you run an OLS it only runs on observations for which all
>>> data is available.
>>>
>>> Try seeing if you do by using -codebook [varname]- , it will tell you if
>>> it holds any missing values. Hope this helps :)
>>>
>>> Arya Eskamani, M.S.
>>> Project Manager
>>> 4700 Millenia Blvd | Ste 500 | Orlando, FL 32839
>>> 407.367.2880 Phone | 877.313.4412 eFax
>>> www.assist-rx.com | arya.eskamani@assist-rx.com
>>>
>>>
>>>
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