Biological variation: evaluation of methods for constructing confidence intervals for estimates of within-person biological variation for different distributions of the within …
T Røraas, B Støve, PH Petersen, S Sandberg - Clinica Chimica Acta, 2017 - Elsevier
T Røraas, B Støve, PH Petersen, S Sandberg
Clinica Chimica Acta, 2017•ElsevierBackground Precise estimates of the within-person biological variation, CV I, can be
essential both for monitoring patients and for setting analytical performance specifications.
The confidence interval, CI, may be used to evaluate the reliability of an estimate, as it is a
good measure of the uncertainty of the estimated CV I. The aim of the present study is to
evaluate and establish methods for constructing a CI with the correct coverage probability
and non-cover probability when estimating CV I. Method Data based on 3 models for …
essential both for monitoring patients and for setting analytical performance specifications.
The confidence interval, CI, may be used to evaluate the reliability of an estimate, as it is a
good measure of the uncertainty of the estimated CV I. The aim of the present study is to
evaluate and establish methods for constructing a CI with the correct coverage probability
and non-cover probability when estimating CV I. Method Data based on 3 models for …
Background
Precise estimates of the within-person biological variation, CVI, can be essential both for monitoring patients and for setting analytical performance specifications. The confidence interval, CI, may be used to evaluate the reliability of an estimate, as it is a good measure of the uncertainty of the estimated CVI. The aim of the present study is to evaluate and establish methods for constructing a CI with the correct coverage probability and non-cover probability when estimating CVI.
Method
Data based on 3 models for distributions for the within-person effect were simulated to assess the performance of 3 methods for constructing confidence intervals; the formula based method for the nested ANOVA, the percentile bootstrap and the bootstrap-t methods.
Results
The performance of the evaluated methods for constructing a CI varied, both dependent on the size of the CVI and the type of distributions. The bootstrap-t CI have good and stable performance for the models evaluated, while the formula based are more distribution dependent. The percentile bootstrap performs poorly.
Conclusion
CI is an essential part of estimation of the within-person biological variation. Good coverage probability and non-cover probabilities for CI are achievable by using the bootstrap-t combined with CV-ANOVA. Supplemental R-code is provided online.
Elsevier
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