quartiles for categorical variable

[sfo]

Is there a way to divide the categorical into 4 quartiles?

For example I have gender with values F and M and I need to divide all F in 4 quartiles and all M in 4 quartiles.

I know for numeric we can use proc rank but what is the equivalent for categorical?

Thanks

[ballardw]

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@sfo wrote:

Is there a way to divide the categorical into 4 quartiles?

For example I have gender with values F and M and I need to divide all F in 4 quartiles and all M in 4 quartiles.

I know for numeric we can use proc rank but what is the equivalent for categorical?

Thanks

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I think you need to provide some example data and what you want the output to look like given that example data. You are using "quartile" in a non-standard way so a more specific example will be helpful.

Do you mean to assign the data into 4 groups fore each sex that are roughly the same size? Does the assignment have to be random? If so perhaps:

Proc sort data=have;

   by sex;

run;

Proc surveyselect data=have out=want groups=4;

   strata sex;

run;

[sfo]

Thanks for the solution.

Does it work on 9.2?

I am getting an error:

436 Proc surveyselect data=fdaada_popPK out=want groups=4;
------
22
ERROR 22-322: Syntax error, expecting one of the following: ;, (, CERTAIN, CERTSIZE, DATA, JTPROBS, M, MAXSIZE, METHOD,
MINSIZE, N, NMAX, NMIN, NOPRINT, OUT, OUTALL, OUTHITS, OUTSEED, OUTSIZE, OUTSORT, RATE, REPS, SAMPRATE, SAMPSIZE,
SEED, SELECTALL, SORT, SRSALG, STATS.

[ballardw]

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@sfo wrote:

Thanks for the solution.

Does it work on 9.2?

I am getting an error:

436 Proc surveyselect data=fdaada_popPK out=want groups=4;
------
22
ERROR 22-322: Syntax error, expecting one of the following: ;, (, CERTAIN, CERTSIZE, DATA, JTPROBS, M, MAXSIZE, METHOD,
MINSIZE, N, NMAX, NMIN, NOPRINT, OUT, OUTALL, OUTHITS, OUTSEED, OUTSIZE, OUTSORT, RATE, REPS, SAMPRATE, SAMPSIZE,
SEED, SELECTALL, SORT, SRSALG, STATS.

---

No, the Groups=option was added in 9.3 (I think).

If Randomness is not an issue this is another way:

Using a SAS set you should have as a starting point:

proc sort data=sashelp.class out=work.class;
   by sex;
run;

data work.want;
   set work.class;
   by sex;
   group= mod(_n_,4)+1;
run;

Which will evenly distribute the group identifier within the BY variable.

[PaigeMiller]

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@ballardw wrote:

If Randomness is not an issue this is another way:

Using a SAS set you should have as a starting point:

proc sort data=sashelp.class out=work.class;
   by sex;
run;

data work.want;
   set work.class;
   by sex;
   group= mod(_n_,4)+1;
run;

Which will evenly distribute the group identifier within the BY variable.

---

And if randomness is an issue, then you can assign random numbers to each observation and use those to split the data into 4 groups.

[PaigeMiller]

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@sfo wrote:

For example I have gender with values F and M and I need to divide all F in 4 quartiles and all M in 4 quartiles.

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Using what criteria would you do this dividing into quartiles? Explain please! Give an example.