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The reported sample probabilities are based on the annual IAB Establishment Panel (IAB-Betriebspanel), 2005 2013, unweighted data aQuestions on pact status are asked in the 2006, 2008, 2009, and 2013 waves of the IAB Establishment Panel bQuestions on opening clause status are asked in the 2005, 2007, and 2011 waves of the IAB Establishment Panel.
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The spatial sampling probabilities are computed by using a normalized exponential loss function.
At the end of each iteration, sampling probabilities are updated according to (11).
For less established methods, such as RDS, the sampling probabilities are not yet well understood and multiple methods of calculating variance may exist with no agreed upon best approach.
Although RI and CC have similar performance when the sample probability is large, RI outperforms CC when σ≤0.03.
wRI has a similar performance with RI when the sample probability is small (=0.01) but becomes much worse when the sample probability increases.
When the sample probability is larger than 6%, the average distance becomes stable which means that a small number of infected nodes is enough to obtain a good estimator.
The case of unknown measurement sampling probabilities is also considered.
For community-living children, sampling probabilities were not available since the sampling frame was not always known.
Inverse sampling probabilities were used as weights with a design of stratified sampling without replacement.
Sampling probabilities were based on the distribution of age, sex, and race/ethnicity of non-attenders.
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