A data scientist uses PROC SURVEYSELECT in SAS to create a stratified random sample for model building, stratifying by a 'region' variable. Which option ensures proportional allocation across strata?
Select an answer to reveal the explanation.
Short Explanation
Here's the deal — you use ALLOC=PROP in the STRATA statement to spread the total sample across regions in proportion to each region's size. That's proportional allocation.
Full Explanation
The correct choice is ALLOC=PROP in the STRATA statement. It allocates the total sample across region strata in proportion to stratum size, which is proportional allocation. PROC SURVEYSELECT also uses SAMPRATE= in the STRATA statement, or overall in the PROC SURVEYSELECT statement, to specify sampling proportion; applying the same rate to all strata yields proportional allocation, with each stratum contributing observations proportional to its size. The ALLOC=NEYMAN in the STRATA statement choice is wrong because it requests Neyman allocation, not proportional allocation. The METHOD=STRATIFIED in the PROC SURVEYSELECT statement choice is wrong because METHOD= specifies the sampling design, such as simple random or systematic sampling, not stratum allocation. The STRATIFY=PROPORTIONAL in the PROC SURVEYSELECT statement choice is wrong because it is not valid syntax; stratification is handled in the STRATA statement.