On Jones et al.’s method for extending Bland-Altman plots to limits of agreement with the mean for multiple observers

Christensen, Henrik Bærbak; Borgbjerg, Jens; Børty, Lars; Bøgsted, Martin

doi:10.1186/s12874-020-01182-w

Cited by 22 publications

(18 citation statements)

References 13 publications

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“…A consequence of this greater similarity would be a decrease in the uncertainty and, therefore, a decrease in the CI widths. A peculiarity of the computational procedure by Christensen et al is that σ̂ normalB 2 can be negative, which we see in three of the samples in Table S2. Using the ICC( A ,1) values to back-calculate the value of σ̂ normalB 2 , we found σ̂ normalB 2 values between −2 × 10 –4 and −9 × 10 –4 , suggesting that their σ̂ normalB 2 are probably close to zero for these cases (GR-Q, DE, and CA-Q).…”

Section: Resultsmentioning

confidence: 81%

“…A consequence of this greater similarity would be a decrease in the uncertainty and, therefore, a decrease in the CI widths. A peculiarity of the computational procedure by Christensen et al 34 is that B 2 can be negative, which we see in three of the samples in Table S2. Using the ICC(A,1) values to back-calculate the value of From Table S2, we found that pollen-free DNA analyses yielded fewer N − 1 genera relative to their pollen DNA counterparts, indicating that pollen-free DNA approaches are more variable across replicates.…”

Section: ■ Resultsmentioning

confidence: 82%

“…The repeatability of replicates processed for pollen DNA and pollen-free DNA isolated from five honey samples was assessed using agreement plotsBland-Altman plots extended to multiple observersvia the R package loamr . To prepare the agreement plot, raw read counts aggregated by genus i and sorted in decreasing overall abundance were converted into additive log ratios of counts x , that is, log 10 ( x ij / x Dj ), where x Dj is the number of counts of replicate j in most abundant genus overall D .…”

Section: Methodsmentioning

confidence: 99%

“…The repeatability of replicates processed for pollen DNA and pollen-free DNA isolated from five honey samples was assessed using agreement plots�Bland-Altman plots extended to multiple observ-ers�via the R package loamr. 34 To prepare the agreement plot, raw read counts aggregated by genus i and sorted in decreasing overall abundance were converted into additive log ratios of counts x, that is, log 10 (x ij /x Dj ), where x Dj is the number of counts of replicate j in most abundant genus overall D. The additive log ratios were filtered for the largest list of N most abundant genera whose Canberra dissimilarity index does not exceed 1. The x-axis shows the mean per genus across replicates, while the y-axis displays the differences of these replicates with respect to the mean per genus.…”

Section: ■ Introductionmentioning

confidence: 99%

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Isolation and Barcoding of Trace Pollen-free DNA for Authentication of Honey

Chavan

Adolacion

Crum

et al. 2022

J. Agric. Food Chem.

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Adulteration and mislabeling of honey to mask its true origin have become a global concern. Pollen microscopy, the current gold standard for identifying honey’s geographical and plant origins, is laborious, requires extensive training, and fails to identify filtered honey and honey spiked with pollen from a more favorable plant to disguise its origins. We successfully isolated pollen-free DNA from filtered honey using three types of adsorbents: (i) anti-dsDNA antibodies coupled to magnetic microspheres; (ii) anion-exchange adsorbent; and (iii) ceramic hydroxyapatite. The internal transcribed spacer 2 region of the captured pollen-free DNA was polymerase chain reaction-amplified and subjected to next-generation sequencing. Using an in-house bioinformatics pipeline, initial experiments showed that anion exchange had the greatest capacity to capture trace pollen-free DNA, and it was successfully applied to isolate DNA from five honey samples. Enrichment of trace pollen-free DNA from filtered honey samples opens a new approach for identifying the true origins of honey.

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Section: Resultsmentioning

confidence: 81%

“…A consequence of this greater similarity would be a decrease in the uncertainty and, therefore, a decrease in the CI widths. A peculiarity of the computational procedure by Christensen et al 34 is that B 2 can be negative, which we see in three of the samples in Table S2. Using the ICC(A,1) values to back-calculate the value of From Table S2, we found that pollen-free DNA analyses yielded fewer N − 1 genera relative to their pollen DNA counterparts, indicating that pollen-free DNA approaches are more variable across replicates.…”

Section: ■ Resultsmentioning

confidence: 82%

Section: Methodsmentioning

confidence: 99%

Section: ■ Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Isolation and Barcoding of Trace Pollen-free DNA for Authentication of Honey

Chavan

Adolacion

Crum

et al. 2022

J. Agric. Food Chem.

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“…When the LoA are smaller than a given tolerance (differences small enough to be considered clinically unimportant) the two techniques are assumed to have acceptable equivalence [9,10,11]. More recently, confidence intervals were added around the upper and lower LoA [12,13,14,15]. Although providing a little more room for the tolerance, LoAs may be regarded as a statistical test for the band limits but do not provide any decision for the technique's equivalence.…”

Section: Introductionmentioning

confidence: 99%

Accuracy, Precision, And Agreement Statistical Tests For Bland-Altman Method

Silveira

Vieira

Ferraro

et al. 2021

Preprint

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Background: Bland and Altman plot method is a widely cited graphical approach to assess equivalence of quantitative measurement techniques. Perhaps due to its graphical output, it has been widely applied, however often misinterpreted by lacking of inferential statistical support. To compare data sets obtained from two measurement techniques, researchers may apply Pearson’s correlation, ordinal least-square linear regression, or the Bland-Altman plot methods, failing to locate the weakness of each measurement technique. We aim to develop and distribute a statistical method in R in order to add robust and suitable inferential statistics of equivalence. Methods: Three nested tests based on structural regressions are proposed to assess the equivalence of structural means (accuracy), equivalence of structural variances (precision), and concordance with the structural bisector line (agreement in measurements of data pairs obtained from the same subject) to reach statistical support for the equivalence of measurement techniques. Graphical outputs illustrating these three tests were added to follow Bland and Altman’s principles of easy communication. Results: Statistical p-values and robust approach by bootstrapping with corresponding graphs provide objective, robust measures of equivalence. Five pairs of data sets were analyzed in order to criticize previously published articles that applied the Bland and Altman’s principles, thus showing the suitability of the present statistical approach. In one case it was demonstrated strict equivalence, three cases showed partial equivalence, and one case showed poor equivalence. Package containing open codes and data is available with installation instructions on SourceForge for free distribution. Conclusions: Statistical p-values and robust approach assess the equivalence of accuracy, precision, and agreement for measurement techniques. Decomposition in three tests helps the location of any disagreement as a means to fix a new technique.

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Defining tumor growth in vestibular schwannomas: a volumetric inter-observer variability study in contrast-enhanced T1-weighted MRI

Cornelissen,

Schouten,

Langenhuizen

et al. 2024

Neuroradiology

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Purpose For patients with vestibular schwannomas (VS), a conservative observational approach is increasingly used. Therefore, the need for accurate and reliable volumetric tumor monitoring is important. Currently, a volumetric cutoff of 20% increase in tumor volume is widely used to define tumor growth in VS. The study investigates the tumor volume dependency on the limits of agreement (LoA) for volumetric measurements of VS by means of an inter-observer study. Methods This retrospective study included 100 VS patients who underwent contrast-enhanced T1-weighted MRI. Five observers volumetrically annotated the images. Observer agreement and reliability was measured using the LoA, estimated using the limits of agreement with the mean (LOAM) method, and the intraclass correlation coefficient (ICC). Results The 100 patients had a median average tumor volume of 903 mm3 (IQR: 193–3101). Patients were divided into four volumetric size categories based on tumor volume quartile. The smallest tumor volume quartile showed a LOAM relative to the mean of 26.8% (95% CI: 23.7–33.6), whereas for the largest tumor volume quartile this figure was found to be 7.3% (95% CI: 6.5–9.7) and when excluding peritumoral cysts: 4.8% (95% CI: 4.2–6.2). Conclusion Agreement limits within volumetric annotation of VS are affected by tumor volume, since the LoA improves with increasing tumor volume. As a result, for tumors larger than 200 mm3, growth can reliably be detected at an earlier stage, compared to the currently widely used cutoff of 20%. However, for very small tumors, growth should be assessed with higher agreement limits than previously thought.

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On Jones et al.’s method for extending Bland-Altman plots to limits of agreement with the mean for multiple observers

Cited by 22 publications

References 13 publications

Isolation and Barcoding of Trace Pollen-free DNA for Authentication of Honey

Isolation and Barcoding of Trace Pollen-free DNA for Authentication of Honey

Accuracy, Precision, And Agreement Statistical Tests For Bland-Altman Method

Defining tumor growth in vestibular schwannomas: a volumetric inter-observer variability study in contrast-enhanced T1-weighted MRI

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