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st: AW: RE: AW: correlate lag variables


From   "Martin Weiss" <martin.weiss1@gmx.de>
To   <statalist@hsphsun2.harvard.edu>
Subject   st: AW: RE: AW: correlate lag variables
Date   Mon, 10 May 2010 18:54:13 +0200

<> 

" I'm coning into this a little late, but did anyone notice that when you
include lag 2 you have 225 observations and when you include only lag 1, you
have 265.  "


That resembles Nick`s point in
http://www.stata.com/statalist/archive/2010-05/msg00471.html closely, I
would say.




HTH
Martin


-----Ursprüngliche Nachricht-----
Von: owner-statalist@hsphsun2.harvard.edu
[mailto:owner-statalist@hsphsun2.harvard.edu] Im Auftrag von Lachenbruch,
Peter
Gesendet: Montag, 10. Mai 2010 18:51
An: 'statalist@hsphsun2.harvard.edu'
Betreff: st: RE: AW: correlate lag variables

I'm coning into this a little late, but did anyone notice that when you
include lag 2 you have 225 observations and when you include only lag 1, you
have 265.  Setting es=e(sample) after the lag 2 analysis and rerunning the
correlation for lag 1 if es==1 might shed some light on the problem.

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 Martin Weiss
Sent: Monday, May 10, 2010 1:24 AM
To: statalist@hsphsun2.harvard.edu
Subject: st: AW: correlate lag variables


<> 

Try -pwcorr- instead:



*************
clear*
set obs 100
gen y=1
replace y =.6*y[_n-1]+rnormal() in 2/l
gen byte time=_n
tsset time
corr y L.y L2.y
pwcorr y L.y
pwcorr y L.y L2.y
*************



HTH
Martin

-----Ursprüngliche Nachricht-----
Von: owner-statalist@hsphsun2.harvard.edu
[mailto:owner-statalist@hsphsun2.harvard.edu] Im Auftrag von Julia
Gesendet: Montag, 10. Mai 2010 10:17
An: statalist@hsphsun2.harvard.edu
Betreff: st: correlate lag variables

Dear all,

I would like to calculate the correlation between a variable and its
past values. Thus, I use the following command:

. correlate BI L1.BI L2.BI
(obs=225)

             |           L.      L2.
             | BI       BI      BI
-------------+---------------------------
          BI|
         --. |   1.0000
         L1. |   0.0111   1.0000
         L2. |   0.0647   0.0161   1.0000


However, if I only ask the correlation for the first lag, my result
differs....

. correlate BI L1.BI
(obs=265)

             |             L.
             |    BI     BI
-------------+------------------
          BI|
         --. |   1.0000
         L1. |   0.0174   1.0000

 Why does excluding the second lag affect the correlation between the
variable and its first lag?

Best regards,

Julia

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