Statistical power calculation and sample size determination for environmental studies with data below detection limits

Shao, Quanxi and Wang, You-Gan (2009) Statistical power calculation and sample size determination for environmental studies with data below detection limits. Water Resources Research, 45 W09410-1-W09410-8. doi:10.1029/2008WR007563


Author Shao, Quanxi
Wang, You-Gan
Title Statistical power calculation and sample size determination for environmental studies with data below detection limits
Journal name Water Resources Research   Check publisher's open access policy
ISSN 0043-1397
1944-7973
Publication date 2009-09
Sub-type Article (original research)
DOI 10.1029/2008WR007563
Volume 45
Start page W09410-1
End page W09410-8
Total pages 8
Place of publication Washington, DC, United States
Publisher American Geophysical Union
Language eng
Formatted abstract
Power calculation and sample size determination are critical in designing environmental monitoring programs. The traditional approach based on comparing the mean values may become statistically inappropriate and even invalid when substantial proportions of the response values are below the detection limits or censored because strong distributional assumptions have to be made on the censored observations when implementing the traditional procedures. In this paper, we propose a quantile methodology that is robust to outliers and can also handle data with a substantial proportion of below-detection-limit observations without the need of imputing the censored values. As a demonstration, we applied the methods to a nutrient monitoring project, which is a part of the Perth Long-Term Ocean Outlet Monitoring Program. In this example, the sample size required by our quantile methodology is, in fact, smaller than that by the traditional t-test, illustrating the merit of our method.
Keyword Water-quality data
Quantiles
Regression
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status Non-UQ
Additional Notes Article number W09410

Document type: Journal Article
Sub-type: Article (original research)
Collection: School of Mathematics and Physics
 
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Created: Wed, 17 Nov 2010, 13:59:00 EST