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.

Cluster and Multistage Sampling

In most sampling problems the population can be regarded as being composed of a set of groups of elements. One sampling use for such groups is to treat them as strata, as discussed in the previous section. In this case, separate samples are selected from each group. Another sampling use is to treat them as clusters, in which case only a sample of them is included in the survey. If all the elements in selected clusters are included in the sample, the method is known as cluster sampling. If only a sample of elements is taken from each selected cluster, the method is known as two-stage sampling. Often a hierarchy of clusters is used: First some large clusters are selected, next some ...

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