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The other half of the design of network data has to do with what ties or relations are to be measured for the
selected nodes. There are two main issues to be discussed here. In many network studies, all of the ties of a given
type among all of the selected nodes are studied -- that is, a census is conducted. But, sometimes different approaches
are used (because they are less expensive, or because of a need to generalize) that sample ties. There is also
a second kind of sampling of ties that always occurs in network data. Any set of actors might be connected by many
different kinds of ties and relations (. students in a classroom might like or dislike each other, they might
play together or not, they might share food or not, etc.). When we collect network data, we are usually selecting,
or sampling, from among a set of kinds of relations that we might have measured.
table of contents Sampling ties Given a set of actors or nodes, there are several strategies for deciding how to go about collecting measurements on the relations among them. At one end of the spectrum of approaches are "full network" methods. This approach yields the maximum of information, but can also be costly and difficult to execute, and may be difficult to generalize. At the other end of the spectrum are methods that look quite like those used in conventional survey research. These approaches yield considerably less information about network structure, but are often less costly, and often allow easier generalization from the observations in the sample to some larger population. There is no one "right" method for all research questions and problems.
Sampling is the process of selecting units (., people, organizations) from a population of interest so that by studying the sample we may fairly generalize our results back to the population from which they were chosen. Let's begin by covering some of the key terms in sampling like "population" and "sampling frame." Then, because some types of sampling rely upon quantitative models, we'll talk about some of the statistical terms used in sampling . Finally, we'll discuss the major distinction between probability and Nonprobability sampling methods and work through the major types in each.