Estimating the mean of data sets that include measurements below the limit of detection.
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Estimating the mean of data sets that include measurements below the limit of detection.

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Published by National Council of the Paper Industry for Air and Stream Improvement in New York, N.Y. (260 Madison Ave., New York 10016) .
Written in English

Subjects:

  • Environmental chemistry -- Statistical methods.,
  • Estimation theory.

Book details:

Edition Notes

SeriesNCASI technical bulletin ;, no. 621, Technical bulletin (National Council of the Paper Industry for Air and Stream Improvement (U.S.) : 1981 ;, no. 621.
ContributionsNational Council of the Paper Industry for Air and Stream Improvement (U.S.)
Classifications
LC ClassificationsTD899.P3 N34 no. 621, TD193 N34 no. 621
The Physical Object
Pagination1 v. (various pagings) :
ID Numbers
Open LibraryOL1324570M
LC Control Number92201986

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Estimating the mean and standard deviation of environmental data with below detection limit observations: Considering highly skewed data and model misspecification. C. SibertOn the Computation of a 95% Upper Confidence Limit of the Unknown Population Mean Based Upon Data Sets with Below Detection Limit by: Estimating the mean and standard deviation of environmental data with below detection limit observations: Considering highly skewed data and model misspecification Article in Chemosphere Where measurements were below detection, the commonly used substitution of below detection limit data, namely half of the detection limit value, was . studies to estimate the mean survival time after diagnosis, where the survival times may be right censored, was in the s adapted for used for estimating the mean of left-censored datasets. General Concepts There are several factors that influence the bias and overall accuracy of a CDA method. They include the type.

The IDL should always be below the method detection limit, and is not used for compliance data reporting, but may be used for statistical data analysis and comparing the attributes of different instruments. The IDL is similar to the "critical level" and "criterion of detection" as defined in the literature. (Standard Methods, 18th edition File Size: KB. Due to limitations of chemical analysis procedures, small concentrations cannot be precisely measured. These concentrations are said to be below the limit of detection (LOD). In statistical analyses, these values are often censored and substituted with a constant value, such as half the LOD, the LOD divided by the square root of 2, or zero. Kaplan-Meier Method. The Kaplan-Meier method is a nonparametric technique for calculating the (cumulative) probability distribution and for estimating means, sums, and variances with censored data. Originally, the Kaplan-Meier approach was developed for right-censored survival data. More recently, the method was reformulated for left-censored environmental .   Epidemiologic studies often collect quantitative measurement data to improve precision and reduce bias in exposure assessment and in the estimation of the effect of exposure on risk of disease, as measured by odds ratios (Hatch and Thomas ; Sim ).Some measurements serve as biomarkers for “dose”—for example, residual radiation in tooth Cited by:

@article{osti_, title = {Statistical treatment of less than detection limit data for small sample hypothesis testing}, author = {Clarke, J U}, abstractNote = {Statistical comparisons using routine parametric procedures such as t-tests are not possible when samples include less than detection limit (censored) observations, unless.   If you don’t really care whether a few true concentrations are or pCi/L because most of your measurements are in the range anyway and you just want to make sure the really low ones aren’t exerting too much influence, you can just go ahead and impute the negative values, zeros, and ‘below detection limit’ values to. The data sets summarized in Table illustrate these points. All three data sets contain ten observations with a sample mean of 10 and a standard deviation of 2. Set 1 is drawn from a symmetrical population; the data are consistent with a normal distribution and the skewness coefficient 3 is zero. Set 2 is drawn from a population that has a moderate positive skew; the . On the other hand, the AOAC defines limit of detection as the lowest content that can be measured with reasonable statistical certainty and the limit of quantification as the content equal to or greater than the lowest concentration point on the calibration curve [ 2 ]. Finally, the USP [ 7] defines LOD as: the lowest amount of analyte that can Cited by: