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<title>DACSEIS Research Paper Series</title>
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<dc:date>2026-11-07T01:52:24Z</dc:date>
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<title>A comparison of the five Labour Force Surveys of the DACSEIS project from a sampling theory point of view</title>
<link>http://hdl.handle.net/10900/47246</link>
<description>A comparison of the five Labour Force Surveys of the DACSEIS project from a sampling theory point of view
Quatember, Andreas
Labour market data are important for the assessment of the working of the national social and economic policies and as an indicator for social trouble spots. The European Union therefore pays very much attention in the harmonisation of the national Labour Force Surveys to be able to have comparable data of high quality.

In this paper these surveys, that are included in the DACSEIS project (IST-2000-26057) are compared from a sampling theory point of view to show the similiarities as well as the differences of these surveys from this aspect.
</description>
<dc:date>2002-01-01T00:00:00Z</dc:date>
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<item rdf:about="http://hdl.handle.net/10900/47236">
<title>A method of weighting adjustment for survey data subject to nonignorable nonresponse</title>
<link>http://hdl.handle.net/10900/47236</link>
<description>A method of weighting adjustment for survey data subject to nonignorable nonresponse
Zhang, Li-Chun
Weighting adjustment is a standard quasi-randomization approach
for survey data subject to nonresponse Little (1986). The existing
methods are typically based on the assumption that nonresponse is
independent of the survey variable conditional to the auxiliary
variables used to form the adjustment cells. In this paper we
consider nonignorable nonresponse which is independent of certain
auxiliary information conditional to the variable of interest. We
estimate the size of the sample adjustment cells using a method of
moment conditional to the sample. The method relies on only the
nonresponse mechanism, and is independent of the sample design. In
variance estimation, we evaluate the nonresponse effect on
estimation and design, analogously to the concept of design
effect. By comparing the nonresponse effects under a nonignorable
model against those under an ignorable one, we obtain a means of
measuring the effect of nonignorability. We motivate and
illustrate our approach for estimation of household composition.
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<dc:date>2002-01-01T00:00:00Z</dc:date>
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