Hi there,
I have read quite some posts on the topic but I don't seem to find a solution. Please consider the sample below.
In this sample, I have one collaborator ("10065968") which is associated with two inventors (as also indicated by count_invid). In some years, the collaborator is active (case_collab!="") while neither of the inventors is (case_invid==""), in this case in 1997.
Using expand I duplicated (by a factor count_invid) such years in order to be able to have one of these observation per inventor, tag indicates the duplicated observation in this case. Since I am running an analysis at the dyadic level inventor-collaborator, I would like to associate the activity of the collaborator in year 1997 to each of the two inventors, as in "wanted".
In my dataset, I have up to 15 inventors per collaborator so I would need a scalable way to do so.
Thank you so much for any suggestion you can provide,
Best wishes,
Giovanna Capponi
clear
input str10 case_invid str23(inventor wanted) float year str23 collaborator str10 case_collab float count_invid byte tag
"" "" "10000709" 1997 "10065968" "12954" 2 1
"" "" "10158528" 1997 "10065968" "12954" 2 0
"25766" "10000709" "10000709" 2000 "10065968" "" 2 0
"25763" "10000709" "10000709" 2000 "10065968" "" 2 0
"25915" "10000709" "10000709" 2001 "10065968" "" 2 0
"25982" "10000709" "10000709" 2001 "10065968" "" 2 0
"29357" "10000709" "10000709" 2001 "10065968" "" 2 0
"44819" "10000709" "10000709" 2004 "10065968" "48769" 2 0
"44803" "10000709" "10000709" 2004 "10065968" "44803" 2 0
"44819" "10000709" "10000709" 2004 "10065968" "44803" 2 0
"44803" "10000709" "10000709" 2004 "10065968" "48769" 2 0
"44819" "10000709" "10000709" 2004 "10065968" "48471" 2 0
"44803" "10000709" "10000709" 2004 "10065968" "48770" 2 0
"44819" "10000709" "10000709" 2004 "10065968" "48770" 2 0
"44803" "10000709" "10000709" 2004 "10065968" "48471" 2 0
"44803" "10000709" "10000709" 2004 "10065968" "48927" 2 0
"44819" "10000709" "10000709" 2004 "10065968" "48927" 2 0
"44819" "10000709" "10000709" 2004 "10065968" "44819" 2 0
"44803" "10000709" "10000709" 2004 "10065968" "44819" 2 0
"50217" "10000709" "10000709" 2005 "10065968" "50217" 2 0
"50217" "10000709" "10000709" 2005 "10065968" "50213" 2 0
"60823" "10000709" "10000709" 2007 "10065968" "62944" 2 0
"60823" "10000709" "10000709" 2007 "10065968" "57293" 2 0
"60823" "10000709" "10000709" 2007 "10065968" "61848" 2 0
"67824" "10000709" "10000709" 2009 "10065968" "67824" 2 0
"67824" "10000709" "10000709" 2009 "10065968" "68070" 2 0
"67824" "10000709" "10000709" 2009 "10065968" "71017" 2 0
"67824" "10000709" "10000709" 2009 "10065968" "68865" 2 0
"67824" "10000709" "10000709" 2009 "10065968" "70374" 2 0
"67824" "10000709" "10000709" 2009 "10065968" "71003" 2 0
"67824" "10000709" "10000709" 2009 "10065968" "70725" 2 0
"36266" "10158528" "10158528" 2002 "10065968" "35960" 2 0
"36024" "10158528" "10158528" 2002 "10065968" "36030" 2 0
"36266" "10158528" "10158528" 2002 "10065968" "36266" 2 0
"36266" "10158528" "10158528" 2002 "10065968" "36030" 2 0
"36024" "10158528" "10158528" 2002 "10065968" "35960" 2 0
"36024" "10158528" "10158528" 2002 "10065968" "36266" 2 0
"36472" "10158528" "10158528" 2003 "10065968" "36472" 2 0
"36471" "10158528" "10158528" 2003 "10065968" "36472" 2 0
"36472" "10158528" "10158528" 2003 "10065968" "36471" 2 0
"36662" "10158528" "10158528" 2003 "10065968" "36662" 2 0
"36471" "10158528" "10158528" 2003 "10065968" "36411" 2 0
"36662" "10158528" "10158528" 2003 "10065968" "36411" 2 0
"36662" "10158528" "10158528" 2003 "10065968" "36471" 2 0
"36662" "10158528" "10158528" 2003 "10065968" "36472" 2 0
"36472" "10158528" "10158528" 2003 "10065968" "36411" 2 0
"36622" "10158528" "10158528" 2003 "10065968" "36413" 2 0
"36347" "10158528" "10158528" 2003 "10065968" "36472" 2 0
"36347" "10158528" "10158528" 2003 "10065968" "36471" 2 0
"36413" "10158528" "10158528" 2003 "10065968" "36413" 2 0
"36413" "10158528" "10158528" 2003 "10065968" "36472" 2 0
"36472" "10158528" "10158528" 2003 "10065968" "36662" 2 0
"36622" "10158528" "10158528" 2003 "10065968" "36347" 2 0
"36472" "10158528" "10158528" 2003 "10065968" "36347" 2 0
"36471" "10158528" "10158528" 2003 "10065968" "36347" 2 0
"36471" "10158528" "10158528" 2003 "10065968" "36413" 2 0
"36411" "10158528" "10158528" 2003 "10065968" "36662" 2 0
"36347" "10158528" "10158528" 2003 "10065968" "36662" 2 0
"36662" "10158528" "10158528" 2003 "10065968" "36347" 2 0
"36411" "10158528" "10158528" 2003 "10065968" "36413" 2 0
"36413" "10158528" "10158528" 2003 "10065968" "36347" 2 0
"36347" "10158528" "10158528" 2003 "10065968" "36411" 2 0
"36413" "10158528" "10158528" 2003 "10065968" "36471" 2 0
"36411" "10158528" "10158528" 2003 "10065968" "36471" 2 0
"36471" "10158528" "10158528" 2003 "10065968" "36662" 2 0
"36471" "10158528" "10158528" 2003 "10065968" "36471" 2 0
0 Response to Fill missing values by groups
Post a Comment