I agree with Maarten.
The principle is easy: replacing missing with zero is valid whenever
missing really does mean zero. Otherwise, you're just fooling yourself
that any problem is solved. Stata will take zeros literally (here
meaning, numerically). It will have absolutely no sense that you might
mean something else.
Nick
On Wed, Mar 27, 2013 at 1:41 PM, Maarten Buis <maartenlbuis@gmail.com> wrote:
> On Wed, Mar 27, 2013 at 2:28 PM, Frank D Lopresti wrote:
>> I am working with a student whose prof said in a memo "Note: when
>> creating new variables, missing values should be coded as some
>> arbitrary numerical value (e.g., 0) so that cases aren’t dropped in
>> the regression . You can also generate a missing flag for each
>> variable, coded 1 for missing and 0 otherwise, and then include the
>> flags in tandem with the variables for unbiased estimates." Is this a
>> valid method for dealing with missing data I've missed?
>
> In general, this is not a valid way of dealing with missing values.
> Here is an explanation of what happens when you use this method:
> <http://www.stata.com/statalist/archive/2006-09/msg00117.html>
>
> However, there is an exception where this method can be useful, which
> is explained here:
> <http://www.stata.com/statalist/archive/2011-07/msg00456.html>
>
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