The regression estimator in presence of ‘‘not at home’’
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Being temporarily not at home can often cause the impossibility to give out a questionnaire to each
selected unit of a sample; moreover, a high percentage of nonrespondents can strongly affect the
quality of estimates. In order to solve this problem the ‘‘not at home’’ are usually called back until
they become available; however, this methodology highly increases the costs of a survey.
The main idea of this paper traces back to an estimation method early proposed by Politz and Simmons;
in particular, a new estimator, based on the regression method, is proposed, so that the auxiliary
information about the number of evenings spent at home by the units of the target population
can be used. The proposed estimator is shown to be unbiased and more efficient than the one based
only on the responses of the units being at home when first contacted. Moreover, unlike from the
Politz-Simmons estimator, the variance of the proposed estimator can be easily determined and
computed. Finally, in order to discuss the asymptotic properties of the regression estimator, the results
of some simulations are reported; both the proposed estimator and the Politz-Simmons one
turn out to be asymptotically unbiased; however, the regression estimator still proves to be more efficient.
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