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Re: st: Recoding missing variables
Thanks for the reply. I do not want to drop the entire
observation as it has nonmissing values for some other
variables. For examples,
var1 outcome1 var3 var4
obs1 1 2 7 99
obs2 99 99 3 1
obs3 0 2 5 4
obs4 1 0 99 99
For analyses of var1 , i want to include obs1, 3, 4
and for var 3 - obs 1,2, and 3.
However, when i run the regression for outcome1
against var1, var3 or var4, I do not want the "99" to
be included as a legitimate coding for those variables
and hence influence the odds ratio estimate.
Hope that clarifies my question a bit.
--- Robert Brummett <email@example.com> wrote:
> I assigned missing values as ".m" (similar to your
> 99) in one of my
> All you have to do is use the "drop" command.
> In your script, before your tables or regression
> script, type:
> drop if variablex == 99
> where you would replace your variable name for
> This assumes you would not want to use those
> observations for other analysis
> (where other variables may be included you don't
> want to drop).
> There are other ways to ignore those with this
> value, and this assumes that
> no non-missing values are 99 in this variable.
> Let me know if this helps or if you want more ideas
> (other ways are not
> really more complex, but take more time to describe.
> Good luck,
> On 7/15/06, Ashwin Ananthakrishnan
> <firstname.lastname@example.org> wrote:
> > Hi,
> > I have a dataset where currently missing values
> > labelled 99 for all variables (which usually have
> > values between 1-15). Is there anyway I can get
> > to recognize the value 99 as missing variables so
> > they are not included in tables or in regression?
> > Thanks,
> > Ashwin
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