Akaike information criterion ≈ Akaike information criterion
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<b>brms</b>: An <i>R</i> Package for Bayesian Multilevel Models Using <i>Stan</i> Open
The brms package implements Bayesian multilevel models in R using the probabilistic programming language Stan. A wide range of distributions and link functions are supported, allowing users to fit - among others - linear, robust linear, bi…
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Variable selection strategies and its importance in clinical prediction modelling Open
Clinical prediction models are used frequently in clinical practice to identify patients who are at risk of developing an adverse outcome so that preventive measures can be initiated. A prediction model can be developed in a number of ways…
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Burden of Stroke in Europe Open
Background and purpose: Prediction of stroke impact provides essential information for healthcare planning and priority setting. We aim to estimate 30-year projections of stroke epidemiology in the European Union using multiple modeling ap…
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A solution to minimum sample size for regressions Open
Regressions and meta-regressions are widely used to estimate patterns and effect sizes in various disciplines. However, many biological and medical analyses use relatively low sample size (N), contributing to concerns on reproducibility. W…
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Variable selection with stepwise and best subset approaches Open
While purposeful selection is performed partly by software and partly by hand, the stepwise and best subset approaches are automatically performed by software. Two R functions stepAIC() and bestglm() are well designed for stepwise and best…
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A nomogram for predicting overall survival in patients with low‐grade endometrial stromal sarcoma: A population‐based analysis Open
Background Low‐grade endometrial stromal sarcoma (LG‐ESS) is a rare tumor that lacks a prognostic prediction model. Our study aimed to develop a nomogram to predict overall survival of LG‐ESS patients. Methods A total of 1172 patients conf…
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Update: use of the benchmark dose approach in risk assessment Open
The Scientific Committee (SC) reconfirms that the benchmark dose (BMD) approach is a scientifically more advanced method compared to the NOAEL approach for deriving a Reference Point (RP). Most of the modifications made to the SC guidance …
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Forecasting of demand using ARIMA model Open
The work presented in this article constitutes a contribution to modeling and forecasting the demand in a food company, by using time series approach. Our work demonstrates how the historical demand data could be utilized to forecast futur…
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Prediction of whole-body fat percentage and visceral adipose tissue mass from five anthropometric variables Open
In the absence of more objective measures of central obesity and adiposity, WHtR is a suitable proxy measure in both women and men. The proposed DXA-%FM and VAT mass cut-offs require validation in larger studies, but offer potential for im…
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The relative performance of AIC, AIC<sub>C</sub>and BIC in the presence of unobserved heterogeneity Open
Summary Model selection is difficult. Even in the apparently straightforward case of choosing between standard linear regression models, there does not yet appear to be consensus in the statistical ecology literature as to the right approa…
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Testing for Granger Causality in Panel Data Open
With the development of large and long panel databases, the theory surrounding panel causality evolves quickly, and empirical researchers might find it difficult to run the most recent techniques developed in the literature. In this articl…
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Cross validation for model selection: A review with examples from ecology Open
Specifying, assessing, and selecting among candidate statistical models is fundamental to ecological research. Commonly used approaches to model selection are based on predictive scores and include information criteria such as Akaike's inf…
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An Approach for Determining the Number of Clusters in a Model-Based Cluster Analysis Open
To determine the number of clusters in the clustering analysis that has a broad range of applied sciences, such as physics, chemistry, biology, engineering, economics etc., many methods have been proposed in the literature. The aim of this…
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<i>SDMtune</i>: An R package to tune and evaluate species distribution models Open
Balancing model complexity is a key challenge of modern computational ecology, particularly so since the spread of machine learning algorithms. Species distribution models are often implemented using a wide variety of machine learning algo…
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Epidemiological and Clinical Predictors of COVID-19 Open
Background Rapid identification of COVID-19 cases, which is crucial to outbreak containment efforts, is challenging due to the lack of pathognomonic symptoms and in settings with limited capacity for specialized nucleic acid–based reverse …
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Optimized Maxent Model Predictions of Climate Change Impacts on the Suitable Distribution of Cunninghamia lanceolata in China Open
Climate change significantly influences changes in ecological phenomena and processes, such as species distribution and phenology, thus accelerating the rate of species extinction or prosperity. Climate change is considered to be one of th…
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Immune-Related lncRNA to Construct Novel Signature and Predict the Immune Landscape of Human Hepatocellular Carcinoma Open
The signature composed of immune-related long noncoding ribonucleic acids (irlncRNAs) with no requirement of specific expression level seems to be valuable in predicting the survival of patients with hepatocellular carcinoma (HCC). Here, w…
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A review and appraisal of arrival-time picking methods for downhole microseismic data Open
We have evaluated arrival-time picking algorithms for downhole microseismic data. The picking algorithms that we considered may be classified as window-based single-level methods (e.g., energy-ratio [ER] methods), nonwindow-based single-le…
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Validation of the 8th Edition of the UICC/AJCC Staging System for Nasopharyngeal Carcinoma From Endemic Areas in the Intensity-Modulated Radiotherapy Era Open
Background: In this study, we evaluated the 8th edition of the Union for International Cancer Control (UICC)/AJCC staging system for nasopharyngeal carcinoma (NPC) in an endemic area, with the aim of validating its applicability and provid…
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The role of C-reactive protein as a prognostic marker in COVID-19 Open
Background C-reactive protein (CRP) is a non-specific acute phase reactant elevated in infection or inflammation. Higher levels indicate more severe infection and have been used as an indicator of COVID-19 disease severity. However, the ev…
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Assessment and Selection of Competing Models for Zero-Inflated Microbiome Data Open
Typical data in a microbiome study consist of the operational taxonomic unit (OTU) counts that have the characteristic of excess zeros, which are often ignored by investigators. In this paper, we compare the performance of different compet…
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Kinetic Modeling to Explain the Release of Medicine from Drug Delivery Systems Open
Proper medication dissolution must be ensured when developing or manufacturing a new solid dosage form. Quantitative analyses performed in dissolution or release tests become simpler when applying mathematical formulae which represent diss…
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2D and 3D CT Radiomics Features Prognostic Performance Comparison in Non-Small Cell Lung Cancer Open
Both 2D and 3D CT radiomics features have a certain prognostic ability in NSCLC, but 2D features showed better performance in our tests. Considering the cost of the radiomics features calculation, 2D features are more recommended for use i…
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On the prevalence of uninformative parameters in statistical models applying model selection in applied ecology Open
Research in applied ecology provides scientific evidence to guide conservation policy and management. Applied ecology is becoming increasingly quantitative and model selection via information criteria has become a common statistical modeli…
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Asymptotic Equivalence between Cross-Validations and Akaike Information Criteria in Mixed-Effects Models Open
For model selection in mixed effects models, Vaida and Blan chard (2005) demonstrated that the marginal Akaike information criterion is appropriate as to the questions regarding the population and the conditional Akaike information criteri…
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Possible signals of vacuum dynamics in the Universe Open
We study a generic class of time-evolving vacuum models which can provide a\nbetter phenomenological account of the overall cosmological observations as\ncompared to the $\\Lambda$CDM. Among these models, the running vacuum model\n(RVM) ap…
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Practical advice on variable selection and reporting using Akaike information criterion Open
The various debates around model selection paradigms are important, but in lieu of a consensus, there is a demonstrable need for a deeper appreciation of existing approaches, at least among the end-users of statistics and model selection t…
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Quantifying variable importance in a multimodel inference framework Open
Summary The sum of Akaike weights (SW) is often used to quantify relative variable importance (RVI) within the information‐theoretic (IT) multimodel inference framework. A recent study (Galipaud et al . 2014, Methods in Ecology and Evoluti…
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On the significance of periodic signals in noise analysis of GPS station coordinates time series Open
Each of the GPS-derived time series consists of the deterministic (functional) and stochastic part. We propose that the deterministic part includes all periodicities from 1st to 9th harmonics of residual Chandler, tropical and draconitic p…
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Machine Learning for Wind Turbine Blades Maintenance Management Open
Delamination in Wind Turbine Blades (WTB) is a common structural problem that can generate large costs. Delamination is the separation of layers of a composite material, which produces points of stress concentration. These points suffer gr…