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http://dx.doi.org/10.5351/KJAS.2015.28.6.1217

Understanding Complex Design Features via Design Effect Models  

Park, Inho (Department of Statistics, Pukyong National University)
Publication Information
The Korean Journal of Applied Statistics / v.28, no.6, 2015 , pp. 1217-1225 More about this Journal
Abstract
Survey research, data is commonly collected through a sample design with complex design features that allow the relative efficiency on the precision of an estimator to be measured using the concept of the design effect compared to simple random sampling as a reference design. This concept is most useful when the design effect can be expressed as a function of various design features. We propose a design effect formula suitable under a stratified multistage sampling by generalizing Gabler et al. (1999, 2006)'s approaches for multistage sampling. Its use can either guide improvement in the design efficiency when in design stage or enable the evaluation of the adopted design features afterwards.
Keywords
stratified multistage sampling; haphazard weighting; intracluster correlation coefficient; mixed effect model; effective sample size;
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Times Cited By KSCI : 1  (Citation Analysis)
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