Summary
Waist‐to‐height ratio (WHtR) is superior to body mass index and waist circumference for measuring adult cardio‐metabolic risk factors. However, there is no meta‐analysis to evaluate its ...discriminatory power in children and adolescents. A meta‐analysis was conducted using multiple databases, including Embase and Medline. Studies were included that utilized receiver‐operating characteristics curve analysis and published area under the receiver‐operating characteristics curves (AUC) for adiposity indicators with hyperglycaemia, elevated blood pressure, dyslipidemia, metabolic syndrome and other cardio‐metabolic outcomes. Thirty‐four studies met the inclusion criteria. AUC values were extracted and pooled using a random‐effects model and were weighted using the inverse variance method. The mean AUC values for each index were greater than 0.6 for most outcomes including hypertension. The values were the highest when screening for metabolic syndrome (AUC > 0.8). WHtR did not have significantly better screening power than other two indexes in most outcomes, except for elevated triglycerides when compared with body mass index and high metabolic risk score when compared with waist circumference. Although not being superior in discriminatory power, WHtR is convenient in terms of measurement and interpretation, which is advantageous in practice and allows for the quick identification of children with cardio‐metabolic risk factors at an early age.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
Receiver operating characteristic (ROC) analysis is a tool used to describe the discrimination accuracy of a diagnostic test or prediction model. While sensitivity and specificity are the basic ...metrics of accuracy, they have many limitations when characterizing test accuracy, particularly when comparing the accuracies of competing tests. In this article we review the basic study design features of ROC studies, illustrate sample size calculations, present statistical methods for measuring and comparing accuracy, and highlight commonly used ROC software. We include descriptions of multi-reader ROC study design and analysis, address frequently seen problems of verification and location bias, discuss clustered data, and provide strategies for testing endpoints in ROC studies. The methods are illustrated with a study of transmission ultrasound for diagnosing breast lesions.
The empirical likelihood is a powerful nonparametric tool, that emulates its parametric counterpart—the parametric likelihood—preserving many of its large-sample properties. This article tackles the ...problem of assessing the discriminatory power of three-class diagnostic tests from an empirical likelihood perspective. In particular, we concentrate on interval estimation in a three-class receiver operating characteristic analysis, where a variety of inferential tasks could be of interest. We present novel theoretical results and tailored techniques studied to efficiently solve some of such tasks. Extensive simulation experiments are provided in a supporting role, with our novel proposals compared to existing competitors, when possible. It emerges that our new proposals are extremely flexible, being able to compete with contestants and appearing suited to accommodating several distributions, such, for example, mixtures, for target populations. We illustrate the application of the novel proposals with a real data example. The article ends with a discussion and a presentation of some directions for future research.
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NUK, OILJ, SAZU, UKNU, UL, UM, UPUK
Effective detection of pathogens from complex substrates is a challenging task. Molecular approaches such as real‐time PCR can detect pathogens present even in low quantities. However, weak real‐time ...PCR signals, as represented by high cycle threshold (Ct) values, may be questionable. Therefore, setting a reliable Ct threshold to declare a positive reaction is important for specific detection. In this study, five methods were assessed for their performance in determining a Ct cut‐off value. These methods were based on the widely used probability of detection (POD) or receiver‐operating characteristic (ROC) approaches. Two important forest pathogens, Hymenoscyphus fraxineus and Fusarium circinatum, were used to set up three experimental frameworks that combined two types of substrates (seed lots and spore traps) and different PCR machines. The ROC‐based method emerged as the most complete and flexible method under various experimental conditions. It was demonstrated that the ROC method leads to a cut‐off value below which late Ct results can reliably be considered indicative of positive test results. This cut‐off value must be determined for each experimental approach used. The method based on the distribution of a previously determined set of Ct values corresponding to false‐positives appeared to be better adapted to detecting false‐negative results, and thus useful for testing potentially invasive pathogens.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
The area under the receiver operating characteristic curve (AUC) is widely used in evaluating diagnostic performance for many clinical tasks. It is still challenging to evaluate the reading ...performance of distinguishing between positive and negative regions of interest (ROIs) in the nested-data problem, where multiple ROIs are nested within the cases. To address this issue, we identify two kinds of AUC estimators, within-cases AUC and between-cases AUC. We focus on the between-cases AUC estimator, since our main research interest is in patient-level diagnostic performance rather than location-level performance (the ability to separate ROIs with and without disease within each patient). Another reason is that as the case number increases, the number of between-cases paired ROIs is much larger than the number of within-cases ROIs. We provide estimators for the variance of the between-cases AUC and for the covariance when there are two readers. We derive and prove the above estimators’ theoretical values based on a simulation model and characterize their behavior using Monte Carlo simulation results. We also provide a real-data example. Moreover, we connect the distribution-based simulation model with the simulation model based on the linear mixed-effect model, which helps better understand the sources of variation in the simulated dataset.
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NUK, OILJ, SAZU, UKNU, UL, UM, UPUK
The area under the receiver operating characteristic (ROC) curve (AUC) is commonly used for assessing the discriminative ability of prediction models even though the measure is criticized for being ...clinically irrelevant and lacking an intuitive interpretation. Every tutorial explains how the coordinates of the ROC curve are obtained from the risk distributions of diseased and non-diseased individuals, but it has not become common sense that therewith the ROC plot is just another way of presenting these risk distributions. We show how the ROC curve is an alternative way to present risk distributions of diseased and non-diseased individuals and how the shape of the ROC curve informs about the overlap of the risk distributions. For example, ROC curves are rounded when the prediction model included variables with similar effect on disease risk and have an angle when, for example, one binary risk factor has a stronger effect; and ROC curves are stepped rather than smooth when the sample size or incidence is low, when the prediction model is based on a relatively small set of categorical predictors. This alternative perspective on the ROC plot invalidates most purported limitations of the AUC and attributes others to the underlying risk distributions. AUC is a measure of the discriminative ability of prediction models. The assessment of prediction models should be supplemented with other metrics to assess their clinical utility.
The area under the curve (AUC) of the receiving‐operating characteristic (or certain modifications of it) is almost universally used to assess the performance of species distribution models (SDMs), ...despite the well‐recognized problems encountered with this approach, mainly present when dealing with presence‐only data.
We present a probabilistic treatment of the presence‐only problem and derive a method to assess the performance of SDMs based on the analysis of an area‐presence plot and the SDM outputs represented in both geographic and environmental spaces.
We show how our method is useful to solve the two main tasks for which the AUC is used: assessing the performance of an SDM and comparing the performance of different SDMs. Our results build on previous work and constitute a rigorous method for assessing the performance of SDMs in relation to a random classifier.
We establish comparisons with two of the most popular approaches used to assess the performance of an SDM, the AUC and the Boyce index, and identified cases in which our method has advantages over these two approaches.
We suggest that the performance of an algorithm that classifies presence‐only data can be assessed by two factors: (a) the degree of non‐randomness of the classification at every step in the accumulation curve of presences, and (b) the amount of uninformative niche space used for the classification. The method we developed can be applied to any SDM output by using the R functions available at: https://github.com/LauraJim/SDM‐hyperTest.
Resumen
Diferentes versiones de la curva ROC (Receiver Operating Characteristic, o Característica Operativa del Receptor) y el área bajo esta curva son usadas comúnmente para evaluar el desempeño de modelos de distribución de especies, a pesar de que algunos estudios han demostrado que estos métodos no son los más adecuados cuando sólo se cuenta con datos de presencia de la especie.
En este trabajo presentamos un modelo de probabilidad que aborda el problema de la evaluación de modelos de distribución basados en datos ocurrencia de la especie. En particular, desarrollamos una metodología que nos permite determinar si el modelo es significativamente mejor que un modelo que predice ocurrencias al azar a partir del análisis de una curva de acumulación de ocurrencias y de los niveles de adecuación predichos por el modelo tanto en el espacio geográfico como en el espacio de nicho.
Mostramos que nuestro método es útil para resolver los dos objetivos principales para los que se usa el área bajo la curva ROC: evaluar el desempeño de un modelo de distribución y comparar diferentes modelos de distribución para una especie.
Con el propósito de identificar las ventajas de la metodología propuesta, realizamos un análisis comparativo con dos de las metodologías más populares en área de modelos de distribución de especies, el área bajo la curva ROC y el índice de Boyce.
Proponemos que el desempeño de un modelo basado únicamente en presencias de la especie sea evaluado bajo dos criterios principales: (i) la significancia estadística en cada salto de la curva de acumulación de ocurrencias y (ii) la cantidad de espacio de nicho predicho como inadecuado para la especie. La metodología desarrollada puede ser aplicada a cualquier modelo de distribución usando las funciones de R que están disponibles en: https://github.com/LauraJim/SDM‐hyperTest.
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
As the literature review suggests, most professional voice users, such as teachers and singers, are prone to vocal abuse or misuse and frequently experience vocal fatigue. Therefore, validating the ...Vocal Fatigue Handicap Questionnaire among professional voice users with and without the symptoms of vocal fatigue might provide appropriate external validity of the questionnaire.
The objective of the study was to validate the Kannada version of the Vocal Fatigue Handicap Questionnaire (VFHQ-K) among a cohort of Kannada-speaking primary and secondary school teachers with and without self-reported vocal fatigue symptoms.
This was a validation study.
The study consisted of two groups of participants. Group 1 included 40 teachers with self-reported vocal fatigue symptoms, and Group 2 included 57 teachers without self-reported vocal fatigue symptoms. The VFHQ-K was administered to each participant after obtaining informed consent. The questionnaire was again readministered between 1 and 2 weeks to assess the test-retest reliability. All the responses that were obtained were tabulated for analysis.
The VFHQ-K demonstrated good test-retest reliability, internal consistency, and acceptable discriminant validity. The cutoff value of VFHQ-K obtained in the present study between the teachers with and without self-reported symptoms of vocal fatigue was much less than the cutoff values reported by the earlier version of VFHQ-K.
The VFHQ-K can be a helpful tool in the early identification of teachers with vocal fatigue and in improving the vocal health of professional voice users.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Although the manufacturers of various electronic components, including pressure sensors, provide us with their operating characteristic, it is necessary to establish it accurately. In this context, ...the paper presents the results obtained following the design and construction of an experimental laboratory stand intended for the experimental determination of the operating characteristics of differential pressure sensors.
Although the manufacturers of various electronic components, including pressure sensors, provide us with their operating characteristic, it is necessary to establish it accurately. In this context, ...the paper presents the results obtained following the design and construction of an experimental laboratory stand intended for the experimental determination of the operating characteristics of differential pressure sensors.
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