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Inferences About Latent Populations From Complex Samples

Mislevy, Robert J.
Publication Year:
Report Number:
ETS Research Report
Document Type:
Page Count:
Subject/Key Words:
Latent Structure, Sampling Design, Statistical Analysis


Standard procedures for drawing inferences from complex samples do not apply when the variables of interest z are not observed directly, but must be inferred from secondary random variables x that depend on z stochastically. Employing Rubin's (1977) approach to missing data in survey research, we present a procedure by which reasonable inferences can be made in such situations. The key is to represent knowledge about latent variables in the form of a predictive distribution, conditional on manifest variables. It is then possible to obtain the expectations of statistics that would have been computed if the values of the latent variables corresponding to sampled units were known, along with variance estimators that account for uncertainty due to both subject sampling and the latency of z. (37pp.)

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