IBM SPSS COMPLEX SAMPLES 19 manual Sampling Wizard Design Variables

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Chapter 2

Sampling Wizard: Design Variables

Figure 2-2

Sampling Wizard, Design Variables step

This step allows you to select stratification and clustering variables and to define input sample weights. You can also specify a label for the stage.

Stratify By. The cross-classification of stratification variables defines distinct subpopulations, or strata. Separate samples are obtained for each stratum. To improve the precision of your estimates, units within strata should be as homogeneous as possible for the characteristics of interest.

Clusters. Cluster variables define groups of observational units, or clusters. Clusters are useful when directly sampling observational units from the population is expensive or impossible; instead, you can sample clusters from the population and then sample observational units from the selected clusters. However, the use of clusters can introduce correlations among sampling units, resulting in a loss of precision. To minimize this effect, units within clusters should be as heterogeneous as possible for the characteristics of interest. You must define at least one cluster variable in order to plan a multistage design. Clusters are also necessary in the use of several different sampling methods. For more information, see the topic Sampling Wizard: Sampling Method on p. 8.