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- W2151202427 abstract "Monte Carlo simulations were used to evaluate statistical methods for estimating 95% upper confidence limits of mean constituent concentrations for left-censored data with nonuniform detection limits. Two primary scenarios were evaluated: data sets with 15 to 50% nondetected samples and data sets with 51 to 80% nondetected samples. Sample size and the percentage of nondetected samples were allowed to vary randomly to generate a variety of left-censored data sets. All statistical methods were evaluated for efficacy by comparing the 95% upper confidence limits for the left-censored data with the 95% upper confidence limits for the noncensored data and by determining percent coverage of the true mean (μ). For data sets with 15 to 50% nondetected samples, the trimmed mean, Winsorization, Aitchison's, and log-probit regression methods were evaluated. The log-probit regression was the only method that yielded sufficient coverage (99–100%) of μ, as well as a high correlation coefficient (r2 = 0.99) and small average percent residuals (− 0.1%) between upper confidence limits for censored versus noncensored data sets. For data sets with 51 to 80% nondetected samples, a bounding method was effective (r2 = 0.96–0.99, average residual = −5% to −7%, 95-98% coverage of μ), except when applied to distributions with low coefficients of variation (standard deviation/μ < 0.5). Thus, the following recommendations are supported by this research: data sets with 15 to 50% nondetected samples—log-probit regression method and use of Chebyshev theorem to estimate 95% upper confidence limits; data sets with 51 to 80% nondetected samples— bounding method and use of Chebyshev theorem to estimate 95% upper confidence limits." @default.
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- W2151202427 date "2006-01-01" @default.
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- W2151202427 title "EVALUATION OF STATISTICAL METHODS FOR LEFT-CENSORED ENVIRONMENTAL DATA WITH NONUNIFORM DETECTION LIMITS" @default.
- W2151202427 doi "https://doi.org/10.1897/05-548r.1" @default.
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