st: RE: RE: Dropping non-consecutive observations in a panel

[Lynnae Ruberg <lruberg@OxfamAmerica.org>]

Many thanks!

-----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Martin Weiss
Sent: Wednesday, June 30, 2010 3:32 PM
To: statalist@hsphsun2.harvard.edu
Subject: st: RE: Dropping non-consecutive observations in a panel


<>


Btw, 11.1 is out, so you should -update all-





***********
clear*

inp byte(id	time	first_time	last_time	a	b	c
)
1	1	1	4	  4	4	0
1	2	1  4  	4	4	0	
1	3	1  4  4	4	0	
1	4	1 4   4	4	0	
2	2	2	4	  3	3	0	
2	3	2	4	  3	3	0	
2	4	2	4	  3	3	0	
3	1	1	4	  3	4	1	
3	3	1	4	  3	4	1	
3	4	1	4	  3	4	1
end

xtset id time
bys id: gen diff=D.time
by id: egen mycount=count(diff)
l, sepby(id)

by id: drop if mycount != _N-1
drop mycount diff
l, sepby(id)
***********


HTH
Martin


-----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu
[mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Lynnae Ruberg
Sent: Mittwoch, 30. Juni 2010 21:20
To: statalist@hsphsun2.harvard.edu
Subject: st: Dropping non-consecutive observations in a panel

Dear Statalist,

I'm relatively new to STATA, so your patience is appreciated.

I'm using STATA/SE 11.0 for Windows to analyze a panel data set. I -xtset-
time and id for the panel. I would like to use only the panels that have
unbroken observations across time - i.e. if id 1 was observed in time
periods 1, 2, and 4, I don't want to use it, but if it was observed in 2, 3,
and 4, then I do.

When I run -xtdescribe- I see that 98% of my data have an unbroken pattern
(like the latter example above). Is there a straightforward way of telling
STATA to only use these & drop (or simply ignore) the rest? Alternatively,
is there a way to browse the data according to the pattern it has in
-xtdescribe-?

Here's the work-around I've come up with for identifying skipped ids, but
I'd love to know if there's any easier way of approaching it.

sort id(time)
by id: gen first_time=time[1]
by id: gen last_time=time[_N]
by id: egen a=count(time)
gen b=(last_time-first_time)+1
gen c=b-a

id	time	first_time	last_time	a	b	c	
1	1	1     	4	      4	4	0
1	2	1	      4      	4	4	0	
1	3	1	      4	      4	4	0	
1	4	1      	4	      4	4	0	
2	2	2     	4	      3	3	0	
2	3	2     	4	      3	3	0	
2	4	2     	4	      3	3	0	
3	1	1     	4	      3	4	1	
3	3	1     	4	      3	4	1	
3	4	1     	4	      3	4	1	

In id==3, time period 2 is skipped; this is "caught" by the different
between the count of time periods per id (variable a) and the total number
of time periods that id is observed - if an id isn't skipped, the difference
will be 0. I'd use -if c==0- in my analysis. Doing it this way identifies
97% of the data as unbroken (so it's not producing the same result as
-xtdescribe-, which I can't figure out).

If there is an easier/more accurate way of doing this, I'd love to know how.

Many thanks,
Lynnae
-------------------------------------------
Lynnae E. Ruberg
Technical Intern
Community Finance Department
Oxfam America

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