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| Introduction to Survey Sampling and Analysis Procedures |
This chapter introduces the SAS/STAT procedures for survey sampling and describes how you can use these procedures to analyze survey data.
Researchers often use sample survey methodology to obtain information about a large population by selecting and measuring a sample from that population. Due to variability among items, researchers apply scientific probability-based designs to select the sample. This reduces the risk of a distorted view of the population and allows statistically valid inferences to be made from the sample. Refer to Cochran (1977), Kalton (1983), and Kish (1965) for more information on statistical sampling. You can use the SURVEYSELECT procedure to select probability-based samples from a study population.
Many SAS/STAT procedures, such as the MEANS and GLM procedures, can compute sample means and estimate regression relationships. However, in most of these procedures, statistical inference is based on the assumption that the sample is drawn from an infinite population by simple random sampling. If the sample is actually selected from a finite population using a complex design, these procedures generally do not calculate the estimates and their variances correctly. The SURVEYMEANS and SURVEYREG procedures do properly analyze survey data, taking into account the sample design. These procedures use the Taylor expansion method to estimate sampling errors of estimators based on complex sample designs.
The following table briefly describes the sampling and analysis procedures in SAS/STAT software.
| 0in.20in SURVEYSELECT | |
| Design Accommodated | stratification |
| clustering | |
| replication | |
| multistage sampling | |
| unequal probabilities of selection | |
| Sampling Methods | simple random sampling |
| unrestricted random sampling (with replacement) | |
| systematic | |
| sequential | |
| selection probability proportional to size (PPS) | |
| with and without replacement | |
| PPS systematic | |
| PPS for two units per stratum | |
| sequential PPS with minimum replacement | |
| SURVEYMEANS | |
| Design Accommodated | stratification |
| clustering | |
| unequal weighting | |
| Available Statistics | population total |
| population mean | |
| proportion | |
| standard error | |
| confident limit | |
| t test | |
| SURVEYREG | |
| Design Accommodated | stratification |
| clustering | |
| unequal weighting | |
| Available Analysis | fit linear regression model |
| regression coefficients | |
| covariance matrix | |
| significance tests | |
| estimable functions | |
| contrasts |
The following sections contain brief descriptions of these procedures.
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