Reviews sampling methods used in surveys: simple random sampling, systematic sampling, stratification, cluster and multi-stage sampling, sampling with probability proportional to size, two-phase sampling, replicated sampling, panel designs, and non-probability sampling. Kalton discusses issues of practical implementation, including frame problems and non-response, and gives examples of sample designs for a national face-to-face interview survey and for a telephone survey. He also treats the use of weights in survey analysis, the computation of sampling errors with complex sampling designs, and the determination of sample size.
The analysis of survey data can employ any of a wide range of statistical techniques, many of which are discussed in other papers in this series. This section does not attempt to review these techniques, but instead discusses only the special considerations involved in analyzing data obtained from a complex sample design. The two topics treated here are the use of weights in survey analysis and the calculation of sampling errors for estimates based on complex sample designs.
Weights are used to assign greater relative importance to some sampled elements than to others in the survey analysis. Weights are needed when the sampled elements are selected by unequal probability sampling; they are also used in poststratification and in making adjustments for total nonresponse. We start ...