you could impute missing data and have a flag variable = 1 if values have been imputed and then ignore the prediction if flag == 1...
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----- Original Message -----
From: "B. Timothy Walsh" <[email protected]>
Date: Thursday, August 6, 2009 11:39 am
Subject: st: "skipping" missing data
To: [email protected]
> 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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