Re: st: RE: Decile sorts

[Jeph Herrin <junk@spandrel.net>]

Oops, don't forget to drop -deciles-

 foreach X of varlist c1* {
    xtile deciles=`X', n(10)
    bys deciles: egen R`X'=mean(`X')
    drop deciles
 }

Jeph Herrin wrote:
> Maybe I'm missing something, but why not:
>
> foreach X of varlist c1* {
>    xtile deciles=`X', n(10)
>    bys deciles: egen R`X'=mean(`X')
> }
>
> ?
>
> hth,
> Jeph
>
>
> Nick Cox wrote:
> > Various comments sprinkled here and there. You may have
> > strong reasons to use these decile bins, but binning strikes me as, 
> > usually, at best a means towards an end (or perhaps ends towards some 
> > means). Some nonparametric
> > regression might do more justice to the data.
> > Also, you are mixing two naming conventions 1...10 and 10...90. Just 
> > use one.
> > Nick n.j.cox@durham.ac.uk
> > Thomas Erdmann
> >  
> > > I am trying to sort my observations into deciles according to one 
> > > attribute
> > > and afterwards calculating the average of another attribute of those 
> > > ten groups. 
> >  
> > > Please find the code I came up with below [lines with ... are 
> > > omitted], yrm is the time variable (YearMonth)
> > >
> > > (1) As far as I can tell it works out, but a) it's a lot of code and
> > > b)produces a lot of variables and c)generating the output is rather 
> > > awkward.
> > >
> > > Could you give me hints on how to implement a smarter solution or if 
> > > there
> > > are any errors in the way the calculation is carried out currently?
> >  
> > > *** Generate Percentiles
> > > sort yrm    
> > >     foreach X of varlist c1* {
> > >     by yrm: egen p10_`X'= pctile(`X'), p(10.0)
> > >     by yrm: egen p20_`X'= pctile(`X'), p(20.0)
> > >     by yrm: egen p30_`X'= pctile(`X'), p(30.0)
> > >     ...
> > >     by yrm: egen p90_`X'= pctile(`X'), p(90.0)
> > >     }
> > This is two loops rolled out into one.
> >     sort yrm     foreach X of varlist c1* {         forval i = 
> > 10(10)90 {             by yrm : egen p`i'_`X' = pctile(`X'), p(`i') 
> >         }
> >     }
> >  
> > > *** Sort into Percentile groups
> > >     foreach X of varlist c1* {
> > >     gen G_`X'=1 if `X'<p10_`X' & `X'~=.
> > >     replace G_`X'=2 if `X'>p10_`X' & `X'<p20_`X'     ...     replace 
> > > G_`X'=9 if `X'>p80_`X' & `X'<p90_`X'     replace G_`X'=10 if 
> > > `X'>p90_`X' & `X'~=.
> > >     }
> > Similar story with boundary conditions.
> >     foreach X of varlist c1* {
> >         gen byte G_`X' = `X' < p10_`X'        
> >         forval i = 2/9 {             local j = 10 * `i'             
> > replace G_`X' = `i' if `X' < p`j'_`X' & G_`X' == 0         }
> >         replace G_`X' = cond(`X' == ., ., 10) if G_`X' == 0     }
> >
> >  
> > > *** Calculate return mean for each group
> > > sort yrm
> > >     foreach X of varlist G* {
> > >     by yrm: egen R1`X'= mean(c1ds_ri) if `X'==1
> > >     by yrm: egen R2`X'= mean(c1ds_ri) if `X'==2
> > >     ...
> > >     by yrm: egen R9`X'= mean(c1ds_ri) if `X'==9
> > >     by yrm: egen R10`X'= mean(c1ds_ri) if `X'==10
> > >     }
> > Why do you need all these variables? The results for bin are disjoint, 
> > so can be put in a single variable.
> >     foreach X of varlist G* {         bysort yrm `X' : egen R`X' = 
> > mean(c1ds_ri)
> >     }
> > Having said that, it can probably done more directly with a series of 
> > -collapse-s.
> > *
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