A NEW COMPRIMISE ALLOCATION METHOD IN STRATIFIED RANDOM SAMPLING

Authors : Sinem Tuğba Şahin Tekin, Yaprak Arzu Özdemir, Cenker Burak Metin

Pages : 181-194

View : 18 | Download : 8

Publication Date : 2017-09-20

Article Type : Research Paper

Abstract :Sample size of the strata is determined by the help of some allocation methods in Stratified Random Sampling. Most of the allocation methods ignore the selection cost. However, in real life applications it is very rare to come across such situations. In this study, a new compromise allocation method is proposed by adding a non-linear cost function constraint to Costa et al.insert ignore into journalissuearticles values(2004); method. Using this new allocation, the sample size with linear cost constraint is also obtained. The performance of the proposed method is studied utilizing the data from Statistics Canada’s Monthly Retail Trade Survey insert ignore into journalissuearticles values(MRTS); of single establishments used by Choudhry et al. insert ignore into journalissuearticles values(2012);.
Keywords : Stratified Random Sampling, Compromise Allocation, Neyman Allocation, Optimum Allocation, Non linear Cost Function