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


From   Richard Goldstein <richgold@ix.netcom.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: RE: RE: sample size reduced significantly
Date   Thu, 11 Apr 2013 17:00:02 -0400

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
>>
>>
>> -----Original Message-----
>> From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-
>> statalist@hsphsun2.harvard.edu] On Behalf Of Yu Chen, PhD
>> Sent: Thursday, April 11, 2013 4:17 PM
>> To: statalist@hsphsun2.harvard.edu
>> Subject: st: sample size reduced significantly
>>
>> Dear Statalist,
>> I have several variables with each of them having at least 6000
>> observations (non-missing values). However, when I put them into OLS
>> regression, the number of observations reduced to only about 1000. I
>> cannot figure out what causes the problem. Could you please help me find
>> out the causes? What code can I use to analyze the problem?
>> Thank you in advance.
>>
>> Yu Chen
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