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Accounting for differences in costs among sampling locations in optimal stratification
Brus, D. J.1,2; Yang, L.3,4; Zhu, A. X.1,4,5
2019
Source PublicationEUROPEAN JOURNAL OF SOIL SCIENCE
ISSN1351-0754
Volume70Issue:1Pages:200-212
Corresponding AuthorBrus, D. J.(dick.brus@wur.nl)
AbstractIn areas with marked differences in accessibility, the cost efficiency of design-based sampling strategies for estimating the population mean or total can be increased by accounting for these differences in the selection of the sampling locations. This can be achieved by stratified random sampling. The question then is how to construct the strata. Existing optimal stratification methods such as cum root f stratification assume a constant cost among the sampling units, and therefore can be suboptimal when this assumption is violated. A simulated annealing algorithm is proposed for simultaneous optimization of the stratum breaks and the sample size under optimal allocation of the sample size, given a chosen maximum for the expected total costs. The proposed stratification method is tested in a study area of 5900 km(2) in Anhui province, China. Optimal stratum breaks were computed for estimating the population mean of the soil organic matter content (SOM). Predictions of SOM from a multiple linear regression model were used as a stratification variable. The optimal stratum breaks differed markedly from the cum root f breaks. The variance of the estimated mean of SOM using the optimal stratification was about 8 to 29% smaller than with the cum root f stratification, depending on the number of strata. This large gain in precision can be explained by the moderately strong correlation of the point-wise costs and the stratification variable. Smaller gains are expected when this correlation is weaker or the variation in costs among the units are smaller. The proposed algorithm can also be used when no ancillary variable related to the variable of interest is available, accounting for differences in costs among the sampling units only. An R script with functions is provided as supporting information.
DOI10.1111/ejss.12731
WOS KeywordSOIL ; VALIDATION ; SCALE
Indexed BySCI
Language英语
Funding ProjectNational Natural Science Foundation of China[41471178] ; National Natural Science Foundation of China[41431177]
Funding OrganizationNational Natural Science Foundation of China
WOS Research AreaAgriculture
WOS SubjectSoil Science
WOS IDWOS:000457540900020
PublisherWILEY
Citation statistics
Document Type期刊论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/49886
Collection中国科学院地理科学与资源研究所
Corresponding AuthorBrus, D. J.
Affiliation1.Nanjing Normal Univ, Sch Geog, Jiangsu Ctr Collaborat Innovat Geog Informat Res, 1 Wenyuan Rd, Nanjing 210023, Jiangsu, Peoples R China
2.Wageningen Univ & Res, Biometris, POB 16, NL-6700 AA Wageningen, Netherlands
3.Nanjing Univ, Sch Geog & Ocean Sci, 163 Xianlin Rd, Nanjing 210023, Jiangsu, Peoples R China
4.Chinese Acad Sci, Inst Geog Sci & Resources Res, State Key Lab Resources & Environm Informat Syst, 11A Datun Rd, Beijing 100101, Peoples R China
5.Univ Wisconsin, Dept Geog, Madison, WI 53706 USA
Recommended Citation
GB/T 7714
Brus, D. J.,Yang, L.,Zhu, A. X.. Accounting for differences in costs among sampling locations in optimal stratification[J]. EUROPEAN JOURNAL OF SOIL SCIENCE,2019,70(1):200-212.
APA Brus, D. J.,Yang, L.,&Zhu, A. X..(2019).Accounting for differences in costs among sampling locations in optimal stratification.EUROPEAN JOURNAL OF SOIL SCIENCE,70(1),200-212.
MLA Brus, D. J.,et al."Accounting for differences in costs among sampling locations in optimal stratification".EUROPEAN JOURNAL OF SOIL SCIENCE 70.1(2019):200-212.
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