<>
Apart from your technical problem, have you considered a panel model for
your estimation? If you predicted out of a fixed effects panel model, that
would be much more straightforward then the current setup...
*************
/*
Dataset from Baum(2006),
http://www.stata-press.com/books/imeus.html
*/
use /*
*/ http://www.stata-press.com/data/imeus/traffic, /*
*/ clear
//slim down substantially
keep if state<6
//individual regressions
qui levelsof state, loc(levels)
foreach sta of local levels{
reg fatal beertax spircons /*
*/ unrate perincK /*
*/ if state==`sta'
}
//fixed effects
xtreg fatal beertax spircons /*
*/ unrate perincK, fe
*************
HTH
Martin
-----Ursprüngliche Nachricht-----
Von: [email protected]
[mailto:[email protected]] Im Auftrag von B. Timothy
Walsh
Gesendet: Donnerstag, 6. August 2009 17:39
An: [email protected]
Betreff: st: "skipping" missing data
I am attempting to generate predictions from regressions performed for each
of a longish list of individuals. The problem is that, for some
individuals, there are no dependent variable data (entries are missing), so
the regression attempt fails. The problem is that the forvalues loop then
exits. I would like to somehow "skip" these individuals. Loop seems to work
fine if there are enough data to perform a regression. I'd be grateful for
any suggestions.
Here's the code:
generate p1=.
forvalues i = 1/50 { //50 individuals
regress bperwk_ wk if ptnum == `i'
predict p
replace p1=p if ptnum == `i'
drop p
}
I'm pretty much a Stata novice. So, I apologize if I am missing something
obvious. Using version 10.1.
Many thanks!
Tim Walsh
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