IBM Water System SPSS COMPLEX SAMPLES 19 User Manual
6
Chapter 2
Sampling Wizard: Design Variables
Figure 2-2
Sampling Wizard, Design Variables step
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.
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.
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.
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.
Method on p. 8.