Thank you, Renzo and Nick. That was most helpful.
Cheers,
Ramani
Nick Cox <[email protected]> wrote:
> Ramani Gunatilaka asked
>
> > I have a data set with consumption and other variables such
> > as number of
> > adults, district, sector for each household.
> > I need to write a programme that requires selecting the
> > particular household
> > whose consumption is nearest to the mean consumption of all
> > the households.
>
> and Renzo Comolli replied
>
> > How do you plan to handle ties (i.e. a case in which there
> > is more than one
> > household which is at the same minimal distance from the average
> > consumption)?
> > If you plan to pick one of them at random then
> > . egen meanconsumption=mean(consumption)
> > . generate absconsumptiondev=abs(meanconsumption-consumption)
> > . sort absconsumptiondev
> > . keep in 1
> > -sort- already does the randomization for you among ties
> >
> > If you plan to keep all the ties
> > . egen meanconsumption=mean(consumption)
> > . generate absconsumptiondev=abs(meanconsumption-consumption)
> > . egen mindevfromavgcons=min(absconsumptiondev)
> > . keep if absconsumptiondev==mindevfromavgcons
>
> In the same spirit, note that you don't need to
> store the mean (which is clearly a constant) in
> a variable.
>
> su consumption, meanonly
>
> produces (silently) a mean accessible immediately
> thereafter as -r(mean)-, so you can then
>
> gen absconsumptiondev = abs(consumption - r(mean))
>
> Similarly, you don't to need to store the
> minimum in a variable, as a similar approach
> could be used. In this case, however,
>
> sort absconsumption
>
> would let you look at the first few households.
>
> The -egen- approach really comes into its own
> when you want to do something like this
> within (e.g.) panels.
>
> Nick
> [email protected]
>
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