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Confidence interval for random‐effects calibration curves with left‐censored data

Aryal, Subhash / Bhaumik, Dulal K. / Santra, Sourav / Gibbons, Robert D.

10.1002/env.920.abs

The presence of left censoring in environmental and engineering applications complicates tests of hypotheses and interval estimation. First, we construct a confidence interval (CI) for a true concentration using nonlinear mixed‐effects regression models for analysis of interlaboratory calibration data with left censoring. Next, we impute the unobserved left‐censored data with randomly simulated value. Finally, we compute the coverage probability via simulation and show that our methodology achieves the nominal level. We illustrate our methodology with a real‐life example. Copyright © 2008 John Wiley & Sons, Ltd.

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Confidence interval for random‐effects calibration curves with left‐censored data

Aryal, Subhash / Bhaumik, Dulal K. / Santra, Sourav / Gibbons, Robert D.

10.1002/env.920.abs

The presence of left censoring in environmental and engineering applications complicates tests of hypotheses and interval estimation. First, we construct a confidence interval (CI) for a true concentration using nonlinear mixed‐effects regression models for analysis of interlaboratory calibration data with left censoring. Next, we impute the unobserved left‐censored data with randomly simulated value. Finally, we compute the coverage probability via simulation and show that our methodology achieves the nominal level. We illustrate our methodology with a real‐life example. Copyright © 2008 John Wiley & Sons, Ltd.

Confidence interval for random‐effects calibration curves with left‐censored data

Aryal, Subhash / Bhaumik, Dulal K. / Santra, Sourav / Gibbons, Robert D.

10.1002/env.920.abs

The presence of left censoring in environmental and engineering applications complicates tests of hypotheses and interval estimation. First, we construct a confidence interval (CI) for a true concentration using nonlinear mixed‐effects regression models for analysis of interlaboratory calibration data with left censoring. Next, we impute the unobserved left‐censored data with randomly simulated value. Finally, we compute the coverage probability via simulation and show that our methodology achieves the nominal level. We illustrate our methodology with a real‐life example. Copyright © 2008 John Wiley & Sons, Ltd.

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Title:

Confidence interval for random‐effects calibration curves with left‐censored data

Contributors:

Aryal, Subhash (author) / Bhaumik, Dulal K. (author) / Santra, Sourav (author) / Gibbons, Robert D. (author)

Published in:

Environmetrics ; 20 ; 181-189

Publication date:

2009-03-01

Size:

9 pages

ISSN:

1099-095X , 1180-4009

DOI:

https://doi.org/10.1002/env.920

Type of media:

Article (Journal)

Type of material:

Electronic Resource

Language:

English

Keywords:

confidence interval , censored data , environmental monitoring , interlaboratory testing

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