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 sampling frame is a major ingredient of the overall sample design. At minimum it provides a means of identifying and locating the population elements, and it usually contains a good deal of additional information that can be used for stratification and clustering. The organization of the frame also often exerts a strong influence on the sample design. Areal clustering is, for instance, greatly assisted by having a frame arranged in suitable geographical units, and stratification is helped by having a frame separated into groups formed by the relevant stratification factors. Frequently listed frames are stored in computer files, with the considerable benefit that they can be readily rearranged to meet sampling requirements.
The ideal sampling frame would list each population element once and once ...