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.
A commonly encountered feature of survey sampling is that a certain amount of information is known about the elements of the population to be studied. In selecting an area sample of the United States, for instance, information is available on the geographical location of the area, whether it is an inner city, suburban or rural area, and census information will provide a wealth of other information about the area—for instance, its population at the previous census, its rate of population change, the proportion of its population employed in manufacturing, and the proportion of its population with race reported as “not white.” Supplementary information of this type can be used either at the design stage to improve the sample design, or at the analysis stage to ...