SAS/STAT^® software includes several procedures for survey data:

• PROC SURVEYSELECT provides a variety of methods for selecting probability-based random samples as well as samples according to a complex multistage design that includes stratification, clustering, and unequal probabilities of selection.
• PROC SURVEYMEANS computes estimates of survey population totals and means, estimates of their variances, confidence limits, and other descriptive statistics.
• PROC SURVEYFREQ produces one-way to n-way frequency and crosstabulation tables for survey data. These tables include estimates of totals and proportions (overall, row percentages, column percentages) and the corresponding standard errors.
• PROC SURVEYREG performs regression analysis for sample survey data, fitting linear models and computing regression coefficients and the covariance matrix.
• PROC SURVEYLOGISTIC performs logistic regression on data that arises from a survey sampling scheme. Variances of the regression parameters and odds ratios are computed using a Taylor expansion approximation.
• Beginning in SAS 9.2 TS2M3, PROC SURVEYPHREG performs regression analysis based on the Cox proportional hazards model for sample survey data. Cox’s semiparametric model is widely used in the analysis of survival data to estimate hazard rates when explanatory variables are available.
• Beginning in SAS 9.4 TS1M3, PROC SURVEYIMPUTE imputes missing values of an item in a sample survey by replacing them with observed values from the same item. Imputation methods include single and multiple hot-deck imputation and fully efficient fractional imputation. Donor selection techniques include simple random selection with or without replacement, probability proportional to weights selection, and approximate Bayesian bootstrap selection.

The SURVEYMEANS, SURVEYFREQ, SURVEYREG, SURVEYLOGISTIC, and SURVEYPHREG procedures can incorporate survey sample designs including designs with stratification, clustering, and unequal weighting.

See this note which discusses and illustrates a method for fitting a Poisson model to count data that are sampled from a finite population using a complex survey design.

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