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On sampling and experiments
Author(s) -
Thompson Steven K.
Publication year - 2002
Publication title -
environmetrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.68
H-Index - 58
eISSN - 1099-095X
pISSN - 1180-4009
DOI - 10.1002/env.532
Subject(s) - sampling (signal processing) , sampling design , sample (material) , selection (genetic algorithm) , computer science , statistics , econometrics , sample size determination , population , mathematics , machine learning , demography , sociology , chemistry , filter (signal processing) , chromatography , computer vision
Sampling generally concerns how a sample of units is selected from a population, while experiments deal with the effects of a treatment or exposure on units and are concerned with the assignment of treatments to units. Real studies typically involve elements of both, with varying control by investigators over sample selection and treatment assignment aspects. Design and model based approaches in sampling and experiments, and in particular studies which combine both elements, are examined in this article. Within a model based approach design based methods can be used based on a conditioning argument which is necessarily somewhat more complex in the case of experimental studies than in studies involving only sampling. Copyright © 2002 John Wiley & Sons, Ltd.