If I understand the sampling plan correctly then you should be subsampling clusters (households) within strata (provinces, etc.). The analysis could look something like this: /* Subsample 30% of clusters (households). Extracts a subsample in dataset subStudy, adds variable SelectionProb */ proc surveySelect data=originalStudy out=subStudy rate=0.3; strata Province; cluster HouseholdID; /* identifies a household within a province */ run; /* Multiply original selection probabilities by subsampling probabilities to create new weights */ data subWeightedStudy; set subStudy; newWeight = originalWeight * SelectionProb; run; /* Estimate means and rates. Households is an optional input dataset that gives the total number of clusters (households) (in variable named _TOTAL_) per stratum (province) */ proc surveyMeans data=subWeightedStudy total=Households; class LifeStyleClass; strata Province; cluster HouseholdID; weight newWeight; var LifeStyleClass HealthVar; /* Estimate LifeStyleClass rates and HealthVar mean */ run; SAS documentation contains a simple example of a stratified cluster sampling design analysis : http://support.sas.com/documentation/cdl/en/statug/63962/HTML/default/viewer.htm#statug_surveymeans_a0000000259.htm PG
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