• The Korean Journal of Applied Statistics
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• v.34 no.5
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• pp.671-683
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• 2021

Power allocation is a technique that evenly allocates samples for each stratum, although the overall efficiency of the allocation is less than that of optimal allocation, and it is often used as a square root proportional allocation in real survey. Also, considering the non-response that occurs in real survey, a larger sample size is used than that in the theoretical formula. In this study, in determining the sample size for each stratum, we study the new methods of allocating by adding information on the response rate per each stratum to power allocation method. The proposed allocation methods are compare with proportional, optimal, and square root proportional allocation in simulation. In addition, the comparison with the proportional and optimal allocation to which the response rate was added is examined through simulation. As a result, we examine the advantages and disadvantages of the allocation methods.

• Journal of the Korean Data and Information Science Society
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• v.27 no.6
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• pp.1443-1452
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• 2016

In this paper, we study a sample design for survey on goodwill in retail properties to provide a protecting policy for small traders and tenants, to use basic data for a dispute case related to goodwill. Since goodwill in retail properties is occurred by individual rent company, we use the census on establishments from the Statistics Korea as population. First of all, we consider preferentially seven metropolitan cities in which there are more than half of population. Total sample size is decided as 8,000. We allocate the sample size for markets as stratum in each city using proportional formula and the sample size for industrial classifications in each market using root proportional formula. Also we compute survey weights and calculate estimators, standard errors and interval of estimators for each characteristic such as type of establishments and market in seven metropolitan cities.

• Journal of the Korean Data and Information Science Society
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• v.21 no.6
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• pp.1021-1029
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• 2010

In 2009 the former three surveys on small and medium enterprises were combined into one survey to reduce the response burden of enterprises. In this report, we study a sample design for 2009 survey on actual state of small and medium enterprises (SMEs). However, the differences between the manufacturing industries and knowledge-based service industries are so large that we need to consider separate populations in the survey. The total sample size is decided as 10,000 in new survey design for integration. We allocate the sample sizes for the first stratum based on CV and then allocate the sample sizes for the second stratum using root proportional formula. Also we calculate survey weights and propose the formula for the estimators as well as standard errors using weights for each characteristic.