Confidence intervals for intraclass correlation coefficients in agreement studies with continuous outcomes are model-specific and no generic approach exists. This paper provides two generic approaches for intraclass correlation coefficients of the form [Formula: see text] The first approach uses Satterthwaite's approximation and an F-distribution. The second approach uses the first and second moments of the intraclass correlation coefficient estimate in combination with a Beta distribution. Both approaches are based on the restricted maximum likelihood estimates for the variance components involved. Simulation studies are conducted to examine the coverage probabilities of the confidence intervals for agreement studies with a mix of small sample sizes. Two different three-way variance components models and balanced and unbalanced one-way random effects models are investigated. The proposed approaches are compared with other approaches developed for these specific models. The approach based on the F-distribution provides acceptable coverage probabilities, but the approach based on the Beta distribution results in accurate coverages for most settings in both balanced and unbalanced designs. A real agreement study is provided to illustrate the approaches.
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http://dx.doi.org/10.1177/0962280214522787 | DOI Listing |
Arch Gynecol Obstet
January 2025
Department of Radiology, National Defense Medical College, 3-2 Namiki, Tokorozawa, Saitama, 359-8513, Japan.
Purpose: To comprehensively compare the diagnostic ability and inter-reader agreement of magnetic resonance imaging (MRI) findings for predicting massive hemorrhage after cesarean section in patients with placental malposition, aiming to identify the most reliable and objective indicators.
Methods: Totally, 148 consecutive patients with placental malposition underwent MRI and cesarean section at our hospital between January 2014 and July 2021. The patients were divided into massive and non-massive hemorrhage groups.
Sci Rep
January 2025
Department of Radiation Oncology, University of Maryland School of Medicine, Baltimore, MD, USA.
The Sharp-van der Heijde score (SvH) is crucial for assessing joint damage in rheumatoid arthritis (RA) through radiographic images. However, manual scoring is time-consuming and subject to variability. This study proposes a multistage deep learning model to predict the Overall Sharp Score (OSS) from hand X-ray images.
View Article and Find Full Text PDFJ Voice
January 2025
Department of Otorhinolaryngology, Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, China. Electronic address:
Objective: The Mandarin Chinese version of the Vocal Performance Questionnaire (VPQ-CM) for evaluating vocal performance.
Methods: A total of 120 participants with vocal disorders and 120 healthy participants completed this study. Investigators translated the original VPQ into the VPQ-CM, and participants completed the questionnaire fill it.
Patients with anterior cruciate ligament reconstruction frequently present asymmetries in the sagittal plane dynamics when performing single leg jumps but their assessment is inaccessible to health-care professionals as it requires a complex and expensive system. With the development of deep learning methods for human pose detection, kinematics can be quantified based on a video and this study aimed to investigate whether a relatively simple 2D multibody model could predict relevant dynamic biomarkers based on the kinematics using inverse dynamics. Six participants performed ten vertical and forward single leg hops while the kinematics and the ground reaction force "GRF" were captured using an optoelectronic system coupled with a force platform.
View Article and Find Full Text PDFInt J Occup Saf Ergon
January 2025
Institute for Future (IFF), Qingdao University, People's Republic of China.
Conventional ergonomic observation methods, such as rapid entire body assessment (REBA), are limited in their sensitivity and reliability, particularly in detecting changes in input variables. This study integrates fuzzy logic with the REBA method, utilizing trapezoidal membership functions to fuzzify the input variables. The center of gravity method was employed for defuzzification, and if-then rules were formulated to enhance the REBA method.
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