# Re: st: RE: Missing values

 From Babigumira Ronnie To statalist@hsphsun2.harvard.edu Subject Re: st: RE: Missing values Date Fri, 28 Jun 2002 01:00:10 -0700 (PDT)

```Nick and Nick
Thanks for the suggestions. Still working on data and will report back on

Roni
--- Nick Cox <n.j.cox@durham.ac.uk> wrote:
> Babigumira Ronnie
>
> > I have data on household expenditure. Households bought "x" kgs (quan)
> of
> > food crops (exp) worth a certain amount of money (unitvalu). However,
> I
> > have cases where the quantity bought is missing (either because the
> > household couldn't recall or an error in data collection) however the
> > amount spent by these households is known. The variables are
> >
> > lc1code   housecode  exp   quan  unitvalu
> > 11233      112331    566    1        500
> >
> > I would like to replace the missing quantities purchased with
> community
> > (lc1code) averages. If the lc1code, food item (exp), unitvalu are the
> same
> > then we can deduce the quantity (quan) that can be purchased by that
> > amount of money. What I now want to do is to replace all missing
> > quantities with a value imputed from community averages. To make it
> more
> > clear
> >
> > If we know that 500/= buys 1kg of cassava in a given community, then a
> > respondent in the community who spends 500/= on cassava should
> > automatically be purchasing 1kg.
> >
> > I want to write a code that would automatically execute this for all
> > missing cases however, I can't figure out where to start. I would
> > appreciate any help.
>
> Nick Winter has made suggestions using -collapse-.
>
> An alternative would be to use -egen-.
>
> Form groups based on your three variables:
>
> egen mean = mean(quan), by(lc1code exp unitvalu)
> replace quan = mean if missing(quan)
>
> However, if this still leaves missing values,
> you might want to go on to a more general regression
> approach.
>
> Nick
> n.j.cox@durham.ac.uk
>
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