Estimation procedures for repeated surveys
Abstract
The aim of this thesis is to examine the methods of estimation
that have been developed for use in sample surveys repeated at
regular intervals, with particular emphasis on the time series
methods that have recently been proposed.
The practice of surveying a population at regular intervals, to
provide timely estimates of characteristics changing over time and
the effects of changing conditions, have been of interest throughout
the relatively short history of the sample survey method. As long
ago as 1942, Jessen showed that by retaining the same sample units
from one survey to the next, an improved population estimate could be
derived, the gain in efficiency being due to the correlation evident
between responses obtained from the same individual unit on different
occasions. This idea led to the wider use of overlapping samples in
repeated surveys and the development of more general estimates to
make efficient use of the overlapping design.
While the correlation between responses given by individual
units in the population was accepted and used, the population
characteristic being estimated was assumed to be a fixed value. Any
correlation between them over time is then ignored. This rather
anamolous situation was pointed out by Blight and Scott (1973) and
estimation procedures have since been developed which incorporate the
stochastic properties of the population characteristic into the
estimates.
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