Errors in variables regression with value-censored data

Samples with analyte concentrations outside a method's dynamic range are a reality of clinical chemistry and are particularly of interest in method comparison studies. The most obvious remedy—to ignore any such values—introduces bias and loses the information that censored data might add to the...

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Bibliographic Details
Published in:Journal of chemometrics 2016-06, Vol.30 (6), p.332-335
Main Authors: Hawkins, Douglas M., Weckwerth, Christina
Format: Article
Language:English
Subjects:
Assaying
Constants
Dynamic range
Errors
Mathematical models
method comparison
Regression
Variance
variance modeling
weighted Deming regression
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Summary:Samples with analyte concentrations outside a method's dynamic range are a reality of clinical chemistry and are particularly of interest in method comparison studies. The most obvious remedy—to ignore any such values—introduces bias and loses the information that censored data might add to the analysis. Extending conventional errors‐in‐variables methods to incorporate value‐censored data recovers this information. The formulation presented uses a variance model more flexible than either the constant variance or the constant coefficient of variation models. Copyright © 2016 John Wiley & Sons, Ltd. Data sets exploring the connection between two assays frequently include samples below the quantitation limit of one or both assays. This paper formulates an approach for weighted errors in variable (weighted Deming) regression to recover information from the samples below the quantitation limit.
ISSN:0886-9383
1099-128X
DOI:10.1002/cem.2797