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Statistical power calculation and sample size determination for environmental studies with data below detection limits
Author(s) -
Shao Quanxi,
Wang YouGan
Publication year - 2009
Publication title -
water resources research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.863
H-Index - 217
eISSN - 1944-7973
pISSN - 0043-1397
DOI - 10.1029/2008wr007563
Subject(s) - quantile , outlier , sample size determination , statistics , statistical power , sample (material) , econometrics , limit (mathematics) , computer science , anomaly detection , data mining , mathematics , mathematical analysis , chemistry , chromatography
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.