ArticleInternational journal of environmental research and public health2020
Nonparametric Limits of Agreement in Method Comparison Studies: A Simulation Study on Extreme Quantile Estimation.
Article in International journal of environmental research and public health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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Who cites it
22 citing papers in PubMed.
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- Frequency-Dependent Diffusion-Relaxation Distribution MRI: Scan-Rescan Reproducibility Ex Vivo and Caveats.NMR in biomedicine · 2026Article
- Precision of automatically generated generic regions of interest for direct assessment of perfusion-MRI.Frontiers in physiology · 2026Article
- Comparison of Transvaginal and Transperineal Ultrasonographic Uterocervical Angle Measurements in Low-Risk Pregnancies at 24-34 Weeks' Gestation.Diagnostics (Basel, Switzerland) · 2025Article
- Invasive validation of novel 1D models for computation of coronary fractional flow reserve.Cardiovascular research · 2025Article
- Development of the Italian version of the modified Barthel index and preliminary reliability in adults with stroke.Journal of rehabilitation medicine · 2025Observational
- From Straight Lines to Curved Paths: Validity and Reliability of Linear Position Transducers to Assess Linear and Angular Motion.Sensors (Basel, Switzerland) · 2025Article
- Ex vivo massively multidimensional diffusion-relaxation correlation MRI: scan-rescan reproducibility and caveats.bioRxiv : the preprint server for biology · 2025Article
- Development of the Italian version of the Motricity Index and evaluation of its reliability in adults with stroke.Journal of rehabilitation medicine · 2025Article
- Comparing Device-Generated and Calculated Bioimpedance Variables in Community-Dwelling Older Adults.Sensors (Basel, Switzerland) · 2024Article
- Evaluating the Usability and Equivalence of Electronic Patient-Reported Outcome Measures for Individuals with a Lower-Limb Amputation.Journal of prosthetics and orthotics : JPO · 2024Article
- Accuracy and Consistency of Confidence Limits for Monosyllable Identification Scores Derived Using Simulation, the Harrell-Davis Estimator, and Nonlinear Quantile Regression.Diagnostics (Basel, Switzerland) · 2024Article
- Assessment of autostereoscopic perception using artificial intelligence-enhanced face tracking technology.PloS one · 2024Article
- Assessing total erythrocyte count as a potential attribute for estimating hemoglobin in Cholistani cattle.Tropical animal health and production · 2023Article
- Assessing Agreement When Agreement Is Hard to Assess-The Agatston Score for Coronary Calcification.Diagnostics (Basel, Switzerland) · 2022Review
- Semi-Automated Quantification of Retinal and Choroidal Biomarkers in Retinal Vascular Diseases: Agreement of Spectral-Domain Optical Coherence Tomography with and without Enhanced Depth Imaging Mode.Diagnostics (Basel, Switzerland) · 2022Article
- A Method to Combine Neurofilament Light Measurements From Blood Serum and Plasma in Clinical and Population-Based Studies.Frontiers in neurology · 2022Article
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Abstract
Bland-Altman limits of agreement and the underlying plot are a well-established means in method comparison studies on quantitative outcomes. Normally distributed paired differences, a constant bias, and variance homogeneity across the measurement range are implicit assumptions to this end. Whenever these assumptions are not fully met and cannot be remedied by an appropriate transformation of the data or the application of a regression approach, the 2.5% and 97.5% quantiles of the differences have to be estimated nonparametrically. Earlier, a simple Sample Quantile (SQ) estimator (a weighted average of the observations closest to the target quantile), the Harrell-Davis estimator (HD), and estimators of the Sfakianakis-Verginis type (SV) outperformed 10 other quantile estimators in terms of mean coverage for the next observation in a simulation study, based on sample sizes between 30 and 150. Here, we investigate the variability of the coverage probability of these three and another three promising nonparametric quantile estimators with n=50(50)200,250(250)1000. The SQ estimator outperformed the HD and SV estimators for n=50 and was slightly better for n=100, whereas the SQ, HD, and SV estimators performed identically well for n≥150. The similarity of the boxplots for the SQ estimator across both distributions and sample sizes was striking.
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