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st: RE: Re: RE: RE: Continous to categorical variable
Yes, something like that would be nice but note that my continous
variable has 62,000 unique values so I cannot do them by hand.
Thank you
Manos
-----Original Message-----
From: [email protected]
[mailto:[email protected]] On Behalf Of Sergiy
Radyakin
Sent: 21 February 2007 17:16
To: [email protected]
Subject: st: Re: RE: RE: Continous to categorical variable
Why would you want to do that?
Would this be something you are looking for?
------------------------------------------
input educ
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
end
hist educ,d
recode educ (1=1) (2 3=2) (4 5 6=3) (7 8 9 10=4) (11 12 13 14=5) (15 16
17=6) (18 19=7) (20=8),gen(educ2)
hist educ2,d
------------------------------------------
Now if you do:
scatter educ educ2
you will realize that you need to place the cut off points at the
quantiles of the normal distribution (transformed properly for your
data)
Sergiy
----- Original Message -----
From: "Mentzakis, Emmanouil" <[email protected]>
To: <[email protected]>
Sent: Wednesday, February 21, 2007 6:03 PM
Subject: st: RE: RE: Continous to categorical variable
> Maybe I should describe a little bit better.
>
> I do not want the variable to "become more like a normal
distribution".
> What I would like is the categories created to be such that the tails
> contain less individuals, with an increase in the numbers as we get
> closer to the middle category.
>
> Thanks
> Manos
>
> -----Original Message-----
> From: [email protected]
> [mailto:[email protected]] On Behalf Of Maarten
Buis
> Sent: 21 February 2007 16:48
> To: [email protected]
> Subject: st: RE: Continous to categorical variable
>
> --- Mentzakis, Emmanouil wrote:
>> I have a continous variable (i.e. income) and I would like to
>> transform it into a categorical one (e.g 5 categories/levels or
more).
>>
>> I would like to ask if there is any way that I can ask stata to
create
>
>> this variable deciding the appropriate cut-off points automatically
so
>
>> that the categories follow aproximately a normal distrubution or they
>> are of equal size.
>
> For the latter have a look at -help egen- and look at the cut
function.
> For the former: how would you expect a variable to become more like a
> normal distribution by making it coarser?
>
> Hope this helps,
> Maarten
>
> -----------------------------------------
> Maarten L. Buis
> Department of Social Research Methodology Vrije Universiteit Amsterdam
> Boelelaan 1081
> 1081 HV Amsterdam
> The Netherlands
>
> visiting address:
> Buitenveldertselaan 3 (Metropolitan), room Z434
>
> +31 20 5986715
>
> http://home.fsw.vu.nl/m.buis/
> -----------------------------------------
>
>
>
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