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Abstract Although unobserved variables go under many names there is a com-
mon structure underlying the problems in which they occur. The purpose of this
Brief is to lay bare that structure and to show that the adoption of a common
viewpoint unifies and simplifies the presentation. Thus, we may acquire an
understanding of many disparate problems within a common framework. The case
of missing observations in a sample is, perhaps, the most obvious example, but the
field of latent variables provides a wider field which also draws attention to the fact
that unobserved variables may be hypothetical as well as ‘real’. Other fields, like
time series analysis, also fit into this framework even though the connection may
not be immediately obvious. The use of these methods has given rise to many
misunderstandings which, we shall argue, often arise because the need for a sta-
tistical, or probability, model is unrecognised or disregarded. A statistical model is
the bridge between intuition and the analysis of data.
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