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Abstract:
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In survey sampling, some populations happen to be hard to reach. Two main reasons are their relative rareness and the absence of a suitable sampling frame. When no sampling frame is available for the desired target population, one can then choose a sampling frame that is indirectly related to this target population. We can then speak of two populations A and B that are related to one another. We wish to produce an estimate for B by selecting a sample from A and using the existing links between the two populations. This is referred to as indirect sampling. Using indirect sampling is one way for surveying hard-to-reach populations. Other approaches such as Network Sampling, Adaptive Cluster Sampling, Snowball Sampling, Respondent-Driven Sampling, and the use of multiple frames exist. Actually, most of these approaches can be put into the context of indirect sampling. One can then use the theory and developments surrounding indirect sampling to obtain a unified mathematical framework for the above approaches. After an overview of indirect sampling and its ready application to hard-to-reach populations, the course will describe indirect sampling in the context of network sampling, adaptive cluster sampling, snowball sampling, respondent-driven sampling, and multiple frames.
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