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.
Although this paper has focused predominantly on probability sampling, the widespread use of nonprobability sampling methodsmakes it inappropriate to avoid mention of them entirely. This section discusses various types of nonprobability sampling, including the widely used technique of quota sampling.
The major strength of probability sampling is that the probability selection mechanism permits the development of statistical theory to examine the properties of sample estimators. Thus estimators with little or no bias can be used, and estimates of the precision of sample estimates can be made. The weakness of all nonprobability methods is that no such theoretical development is possible; as a consequence, nonprobability samples can be assessed only by subjective evaluation. Moreover, even though experience may have shown that a nonprobability method has worked ...