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This is undertaken using two different methodologies of sample selection and analysis: innovative sample selection using GIS to identify hotspots is compared with destination sampling and for analysis the use of time and cost calculations are compared with generalised cost.
Methodologically, the sample selection using a combination of census and GIS to identify "hotspots" was efficient at identifying an appropriate sample with the desired attributes which, in particular, allowed a variety of destinations to be examined.
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To demonstrate the purely spatial sampling selection using VQA, SUNY satellite-derived irradiance over Colorado on 4 September 2004 is used.
In theory, at infinite sample size, model selection using BIC selects the true model if it is included in the search space [56].
A sample selection process, using a modified version of principal component analysis, is employed to select labeled source domain samples such that the source and target marginal distributions are equalized.
The characteristics of the Walkerville sample, close to those characteristics reported by the Census 2001 data, confirm that sample selection by using GIS was efficient.
Specifically, we proposed sample selection methods using (i) repeated random draws, (ii) a genetic algorithm, and (iii) pair-wise sample compatibilities.
The data analysis was done by descriptive statistics and econometric model (Heckman's sample selection model) using STATA 12 and SPSS 19.
We proposed a resampling correction for sample selection bias using a mathematical framework modeling the sampling process.
A purposive sample selection was used to select participants knowledgeable in the understanding of the Bafut Language to participate in focus groups and in-depth interviews and also in their ability to link the names used in addressing diabetes to diagnosis and management of diabetes.
Seven CD19-selected sporadic CLL samples were obtained by positive selection using magnetic beads conjugated to anti-CD19 (MACS, Miltenyi Biotec, Auburn, CA).
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