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RE: st: RE: creating variable summarizing for each individual properties of other members of a group at t-1
From
Erik Aadland <[email protected]>
To
<[email protected]>
Subject
RE: st: RE: creating variable summarizing for each individual properties of other members of a group at t-1
Date
Tue, 17 May 2011 18:13:45 +0000
Thank you so much for your input, Nick.
I have experimented and generated different variables previously relying on the very helpful FAQ in question.
I am struggling with this problem however. When I apply the suggested code below, it appears that the calculation of the number of peers adds up more than it should for ind_ids with more ind_entry = 1 relative to other ind_ids, and consequently contribute more to the "score" than those with fewer ind_entry = 1.
Referring to the example dataset, ind_id 2 is given the correct "prevscore". Ind_id 4, however, is not. By yearmonth 12, ind_id 4 has contributed 2 ind_entry=1 to the "score", which is correct for ind_id 2. However, ind_id 2 has not yet experienced ind_entry=1. Consequently, score - 1 for ind_id 4 yields a score = 1 in yearmonth 11 and 12, when the correct score = 0. And so on.
Here is the suggested code as I applied it:
clear ;
#delimit ;
use "ind_entry_ex.dta" ;
sort yearmonth ;
gen score = sum(ind_entry) ;
by yearmonth: replace score = score[_N] ;
replace score = score - ind_entry ;
bysort ind_id (yearmonth): gen prevscore = score[_n-1] ;
Here is the output:
year month yearmonth ind_id ind_entry score prevscore
2003 10 10 2 0 1
2003 11 11 2 0 1 1
2003 12 12 2 0 2 1
2004 1 13 2 0 2 2
2004 2 14 2 1 2 2
2004 3 15 2 0 3 2
2003 10 10 4 1 0
2003 11 11 4 0 1 0
2003 12 12 4 1 1 1
2004 1 13 4 0 2 1
2004 2 14 4 0 3 2
2004 3 15 4 0 3 3
I use Stata 10.
Thanks again and kind regards,
Erik.
----------------------------------------
> From: [email protected]
> To: [email protected]
> Date: Tue, 17 May 2011 17:47:53 +0100
> Subject: st: RE: creating variable summarizing for each individual properties of other members of a group at t-1
>
> I don't know what "I am familiar with" means here. Does it mean that you've read the FAQ but can't see how to apply it?
>
> This sounds to me like
>
> 1. Get the sum of all individual entries
>
> sort yearmonth
> gen score = sum(ind_entry)
> by yearmonth : replace score = score[_N]
>
> 2. Subtract this individual
>
> replace score = score - ind_entry
>
> 3. Look one step back in time
>
> bysort ind_id (yearmonth) : gen prevscore = score[_n-1]
>
> Nick
> [email protected]
>
> Erik Aadland
>
> I need to create a variable that sums for each individual in my dataset the total number of ind_entry of all other individuals at time: yearmonth - 1.
> I have attached a small ex of my data structure below. So for instance, given the small dataset below, for ind_id 2 in yearmonth 11 this variable score = 1. But for ind_id 4 in the same yearmonth, the score = 0.
>
> I would also like to generate a variable that identifies for each individual the unique number of other individuals in the dataset that have experienced ind_entry = 1 at least once up until time: yearmonth - 1.
>
> I am familiar with the following FAQ: http://www.stata.com/support/faqs/data/members.html
>
> My data structure is snapshot data in principle like the example below, but some individuals enter the observation window later than others (i.e. in later yearmonths):
>
> year month yearmonth ind_id ind_entry
> 2003 10 10 2 0
> 2003 11 11 2 0
> 2003 12 12 2 0
> 2004 1 13 2 0
> 2004 2 14 2 1
> 2004 3 15 2 0
> 2003 10 10 4 1
> 2003 11 11 4 0
> 2003 12 12 4 1
> 2004 1 13 4 0
> 2004 2 14 4 0
> 2004 3 15 4 0
>
>
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