Select at least one item per category radomly, with a minimum % of the whole population

[nicnad]

Hi,

I would like to know the most efficient SAS procedure to select at least one item per category randomly, with a minimum of 50% of the whole population.

To illustrate my problem. Lets say I have the following table :

Category	Info1
Flower	aaa
Flower	bbb
Flower	ccc
Fruit	ddd
Car	ddd
Car	eee
Car	fff
Car	iii
Toy	fff
Toy	ggg

The result would be like the following table (with random values and at least 1 item per category) :

Category	Info1
Flower	aaa
Fruit	ddd
Car	fff
Toy	ggg
Flower	ccc

Thank you for your help and time.

[PGStats · Accepted solution]

Surveyselect with samprate and strata will do exactly what you want:

data have;

input category $ info $;

datalines;

Flower aaa

Flower bbb

Flower ccc

Fruit ddd

Car ddd

Car eee

Car fff

Car iii

Toy fff

Toy ggg

;

proc surveyselect data=have out=want samprate=0.5 seed=114876001;

strata category notsorted;

run;

proc print data=want noobs; run;

PG

[nicnad]

Thank you very much to all of you for your help.

For the proc surveyselect method, when I do not sort my table by the specific variable and use 'notsorted' it doesn't return the appropriate result.

Therefore, when I use a proc sort on my variable, the I use proc surveyselect with mentioning 'notsorted', it works.

As for the modified proc sql method. When I use it in my data, it select one additional record that should not be there...

I would like to know if my manipulation with the proc surveyselect are Ok and what would be the correct method to do it with a proc SQL.

Thanks

[PGStats]

NOTSORTED means that the data from each category occurs together consecutively but not necessarily in sorted order (e.g. aaaa cccc dd bbb).

Post your code.

PG

[nicnad]

Thank you for the quick reply.

I won't post my actual data because it is sensitive, but this example triggers the same problem. If I understand properly, the number of strata should be 4, but it returns "Number of strata = 7".

data have;

input preinfo $ category $ info $;

datalines;

asdfasdfa Flower aaa

asfdasdfasdf Flower bbb

awdfadfasf Flower ccc

fasdfsdafds Fruit ddd

asdsdafsdf Car ddd

asdfasdfs Car eee

asdfasfsdff Car fff

asdfasdfds Car iii

asdfasdf Toy fff

asdfsdaerqwerwefad Toy ggg

asdfasdfa Flower aaa

asfdasdfasdf Flower bbb

awdfadfasf Flower ccc

fasdfsdafds Fruit ddd

asdsdafsdf Car ddd

asdfasdfs Car eee

asdfasfsdff Car fff

asdfasdfds Car iii

;

proc surveyselect data=have out=want samprate=0.1 seed=114876001;

strata category notsorted;

run;

[PGStats]

Yes, since your category data is not consecutive, you need to sort BY category before calling surveyselect.

proc sort data=have; by category; run;

proc surveyselect data=have out=want samprate=0.1 seed=114876001;

strata category;

run;

PG

[nicnad]

Excellent.

Thank you all for your help!

[stat_sas]

proc sql;

select * , rand('UNIFORM') as r

from have

group by category

having r=min(r) or (count(category)>=1 and count(category)<=2);

quit;

[PGStats]

your solution will not work for a general population with larger categories. It will choose a single observation per category, which may be far less than 50%. A simple change to your SQL approach can however yield good samples (without the perfect assurance of a >50% sample size):

data have;

input category $ info $;

datalines;

Flower aaa

Flower bbb

Flower ccc

Fruit ddd

Fruit eee

Fruit fff

Fruit ggg

Fruit hhh

Fruit iii

Fruit jjj

;

/* Modified code */

proc sql;

select * , rand('UNIFORM') as r

from have

group by category

having r=min(r) or r<0.5;

quit;

PG

[stat_sas]

Hi PG,

Yes, that is right. Thanks for the suggestion.

Regards,

Naeem

[PGStats]

Along the same lines, if you want to guarantee a >50% sample, you can use proc rank to create fractional ranks (hint: fractional rank=1 when there is a single case in a category) :

data temp;

call streaminit(987256);

set have;

r = RAND("UNIFORM");

run;

proc rank data=temp out=want(where=(r>0.5)) fraction;

by category notsorted;

var r;

run;

proc print data=want(drop=r) noobs; run;

PG

[RamKumar]

RAND function suppose to generate a random number from a distribution where as it producing all the records from the table (have) when I ran your code. Please advise. I assumed 'have' dataset as below.

data have;

input category $ info $;

datalines;

Flower aaa

Flower bbb

Flower ccc

Fruit ddd

Fruit eee

Fruit fff

Fruit ggg

Fruit hhh

Fruit iii

Fruit jjj

;

Also 'r' value differs when I ran it one variable 'category'.

[PGStats]

I don't understand your question. When I run this (exactly this):

data have;

input category $ info $;

datalines;

Flower aaa

Flower bbb

Flower ccc

Fruit ddd

Fruit eee

Fruit fff

Fruit ggg

Fruit hhh

Fruit iii

Fruit jjj

;

data temp;

call streaminit(987256);

set have;

r = RAND("UNIFORM");

run;

proc rank data=temp out=want(where=(r>0.5)) fraction;

by category notsorted;

var r;

run;

proc print data=want(drop=r) noobs; run;

I get this output:

                                   The SAS System                                  1

                                                  11:15 Thursday, September 25, 2014

                                  category    info

                                   Flower     bbb

                                   Flower     ccc

                                   Fruit      eee

                                   Fruit      hhh

                                   Fruit      iii

                                   Fruit      jjj

The proc rank step replaces the random numbers (r in dataset temp) by their fractional ranks (r in dataset want) and keeps only the fractional ranks greater than 0.5. This way, a random selection of half the observations is kept in each category.

PG