Hi, Apologies if this is a silly question, I am a relatively new SAS user currently running 9.3. I have a dataset (CITIES) of around 20,000 cities, each with population size classification, climate type, and national GDP classification.Some cities in the dataset also have data on transport, health, etc, which I have summarised into a single column called DataCoverage which counts the columns with known data for each city. I'd like to do further analysis on a sub-sample of cities, and I would like to randomly select them in a manner which reflects the existing proportions of the data. I have done: proc surveyselect data = CITIES out = samp1 method = srs sampsize=200 seed = 9876; strata CLIMATE POPULATION_CLASS GDP_CLASS / alloc=proportional; run; What I would really like to do is select a subsample, which represents the proportions of the original dataset, but gives more weight to those with a larger DataCoverage (i.e. more known data, so I don't have to go find the data somewhere myself). Is such a thing possible? Thanks, Jon
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