Abstract
Abstract We discuss some fundamental issues regarding the roles that statistical models play in surveys. Many survey applications “borrow strength” from statistical models such as regression models and mixed effects models, even though these popular statistical models rarely hold exactly, if at all, in the real world. Yet, the idea of borrowing strength carries on, and the practice proves to be useful in many cases. We discuss basic ideas of borrowing strength via a statistical model and suggest practical criteria for evaluating a model, knowing that it is likely to be incorrect in a strict sense. Furthermore, we discuss a model selection strategy, known as the fence methods, which can incorporate practical interests into the selection criterion. Examples are used for illustration. Further remarks on challenging problems are offered.
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