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SURVEYSELECT Procedure


The SURVEYSELECT procedure provides a variety of methods for selecting probability-based random samples. The procedure can select a simple random sample or can sample according to a complex multistage sample design that includes stratification, clustering, and unequal probabilities of selection. With probability sampling, each unit in the survey population has a known, positive probability of selection. This property of probability sampling avoids selection bias and enables you to use statistical theory to make valid inferences from the sample to the survey population. The following are highlights of the SURVEYSELECT procedure's features:

  • selects the sample and produces an output data set that contains the selected units, their selection probabilities, and their sampling weights
  • provides methods for both equal probability sampling and probability proportional to size (PPS) sampling
  • provides the following equal probability sampling methods:
    • simple random sampling
    • unrestricted random sampling (with replacement)
    • systematic random sampling
    • sequential random sampling
    • Bernoulli
  • provides the following unequal probability sampling methods:
    • Poisson sampling
  • provides the following probability proportional to size (PPS) methods:
    • PPS sampling without replacement
    • PPS sampling with replacement
    • PPS systematic sampling
    • PPS algorithms for selecting two units per stratum
    • sequential PPS sampling with minimum replacement
  • performs stratified sampling by selecting samples independently within the specified strata, or nonoverlapping subgroups of the survey population
  • enables you to sort by control variables within strata for the additional control of implicit stratification when using a systematic or sequential selection method
  • provides survey design methods to allocate the total sample size among the strata
  • provides the following allocation methods: proportional, Neyman, and optimal allocation
  • provides replicated sampling, where the total sample is composed of a set of replicates, and each replicate is selected in the same way
  • enables you to randomly assign the observations in the input data set to groups

For further details see the SAS/STAT User's Guide: The SURVEYSELECT Procedure
( PDF | HTML )

Examples