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RE: st: Dropping observations and creating a balanced panel
From
Eric Booth <[email protected]>
To
"[email protected]" <[email protected]>
Subject
RE: st: Dropping observations and creating a balanced panel
Date
Wed, 28 Jul 2010 14:10:07 +0000
<>
Yeah, it was a typo, I meant to type "firstyear" instead of "year" in that last line.
Also, you could also use -fillin- (from SSC) to create balanced panels after dropping
panels that are problematic (start after 2003 & with closure | chow).
cap which fillin
if _rc ssc install fillin, replace
fillin oshpd_fac_no year
~ Eric
________________________________________
From: [email protected] [[email protected]] on behalf of Martin Weiss [[email protected]]
Sent: Wednesday, July 28, 2010 8:48 AM
To: [email protected]
Subject: AW: st: Dropping observations and creating a balanced panel
<>
"I am off to try and figure out the duplicates or some similar command."
You can find the problematic observations thus:
*************
sysuse nlswork,clear
bys idcode: gen int number=_N
su number, mean
cou if number!=r(max)
*************
HTH
Martin
-----Ursprüngliche Nachricht-----
Von: [email protected]
[mailto:[email protected]] Im Auftrag von Matthew
Krauchunas
Gesendet: Mittwoch, 28. Juli 2010 15:27
An: [email protected]
Betreff: Re: st: Dropping observations and creating a balanced panel
Hi Eric,
I had to tweak the code a little bit, but you got me 95% of the way there!
drop if firstyear>2002 & !mi(year)
instead of drop if year>2003 & !mi(year)
My only problem now is that I would expect a balanced panel (i.e., one
divisible by 6), but that is not the case as I have 3,971 observations
remaining. Also, it will not let me xtset the data. Instead it gives
me a "repeated time values within panel error." I am off to try and
figure out the duplicates or some similar command.
Thanks,
Matt
On Tue, Jul 27, 2010 at 9:53 PM, Eric Booth <[email protected]> wrote:
> <>
>
> Note: I added facility 206010741 to your example data:
> *********!
> clear
> inp double(oshpd_fac_no) year chow closure
> 206010734 2002 0 0
> 206010734 2003 0 0
> 206010734 2004 0 0
> 206010734 2006 0 0
> 206010734 2006 1 0
> 206010734 2008 0 0
> 206010744 2002 0 0
> 206010744 2003 0 0
> 206010744 2004 0 0
> 206010744 2007 0 0
> 206010744 2008 0 0
> 206010747 2002 0 0
> 206010747 2003 0 0
> 206010747 2004 0 0
> 206010747 2006 0 0
> 206010747 2007 0 0
> 206010747 2008 0 0
> 206010741 2007 0 0
> 206010741 2004 0 0
> 206010741 2005 0 0
> 206010741 2006 0 0
> end
>
> ** 1. drop all the observations in each of the panels if there was a chow
or closure**
> bys oshpd_fac_no: egen any_chow = max(chow)
> bys oshpd_fac_no: egen any_closure = max(closure)
> drop if 1==any_closure | 1==any_chow
>
> **2. drop if I have all nursing homes that opened after 2003 **
> bys oshpd_fac_no: egen firstyear = min(year)
> drop if year>2003 & !mi(year)
> *********!
>
> ~ Eric
>
> __
> Eric A. Booth
> Public Policy Research Institute
> Texas A&M University
> [email protected]
> Office: +979.845.6754
>
>
> On Jul 27, 2010, at 4:52 PM, Matthew Krauchunas wrote:
>
>> Hello,
>>
>> I am studying nursing homes (2002-2004 & 2006-2008) and I have a two
>> part problem that I need to solve in order to create a balanced panel.
>> First, I have nursing homes that have closed or changed ownership
>> (chow) during my study period. I need to drop all the observations
>> in each of the panels (panel identifier is the oshpd_fac_no) if there
>> was a chow or closure? Second, I have nursing homes that opened after
>> 2003 and therefore I would not have all the observations for these
>> panels. How can I identify and remove these panels as well? Does
>> anyone have any ideas?
>>
>>
>> oshpd_fac_no year chow closure
>> 206010734 2002 0 0
>> 206010734 2003 0 0
>> 206010734 2004 0 0
>> 206010734 2006 0 0
>> 206010734 2006 1 0
>> 206010734 2008 0 0
>> 206010744 2002 0 0
>> 206010744 2003 0 0
>> 206010744 2004 0 0
>> 206010744 2007 0 0
>> 206010744 2008 0 0
>> 206010747 2002 0 0
>> 206010747 2003 0 0
>> 206010747 2004 0 0
>> 206010747 2006 0 0
>> 206010747 2007 0 0
>> 206010747 2008 0 0
>>
>> Thank you,
>> Matt
>> *
>
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