Search · four archives
Search · four archives
23 papers · ranked by Valyu relevance
Kwanghee Jung, Jaehoon Lee, Vibhuti Gupta, Gyeongcheol Cho
Generalized structured component analysis (GSCA) is a theoretically well-founded approach to component-based structural equation modeling (SEM). This approach utilizes the bootstrap method to estimate the confidence intervals of its parameter estimates without recourse to distributional assumptions, such as…
Gabriele Cevenini, Paolo Barbini
Background Scoring systems are a very attractive family of clinical predictive models, because the patient score can be calculated without using any data processing system. Their weakness lies in the difficulty of associating a reliable prognostic probability with each score. In this study a bootstrap approach for…
Stephen J Walters, Michael J Campbell
Health-Related Quality of Life (HRQoL) measures are becoming increasingly used in clinical trials as primary outcome measures. Investigators are now asking statisticians for advice on how to analyse studies that have used HRQoL outcomes. HRQoL outcomes, like the SF-36, are usually measured on an ordinal scale. However…
Nina Deng, Jeroan J Allison, Hua Julia Fang, Arlene S Ash + 1 more
'John E Ware Jr'] Background Relative validity (RV), a ratio of ANOVA F-statistics, is often used to compare the validity of patient-reported outcome (PRO) measures. We used the bootstrap to establish the statistical significance of the RV and to identify key factors affecting its significance. Methods Based on…
Vinícius Litvinoff Justus, Vitor Batista Rodrigues, Alex Rodrigo dos Santos Sousa
'Alex Rodrigo dos Santos Sousa'] Bootstrap is a widely used technique that allows estimating the properties of a given estimator, such as its bias and standard error. In this paper, we evaluate and compare five bootstrap-based methods for making confidence intervals: two of them (Normal and Studentized) based on the…
Weizhen Wang, Chongxiu Yu, Zhongzhan Zhang
A reasonable confidence interval should have a confidence coefficient no less than the given nominal level 1−α and a small expected length to reliably and accurately estimate the parameter of interest, and the bootstrap interval is considered to be an efficient interval estimation technique. In this paper, we offer a…
Manussaya La-ongkaew, Sa-Aat Niwitpong, Suparat Niwitpong, Najat Saliba
'Najat Saliba'] Wind energy is an important renewable energy source for generating electricity that has the potential to replace fossil fuels. Herein, we propose confidence intervals for the difference between the coefficients of variation of Weibull distributions constructed using the concepts of the generalized…
Njesa Totty, James Molyneux, Claudio Fuentes
Bootstrapping and other resampling methods are progressively appearing in the textbooks and curricula of courses that introduce undergraduate students to statistical methods. Though simple bootstrapbased inferential methods may have more relaxed assumptions than their traditional counterparts, they are not quite…
Tim Hesterberg
I have three goals in this article: (1) To show the enormous potential of bootstrapping and permutation tests to help students understand statistical concepts including sampling distributions, standard errors, bias, confidence intervals, null distributions, and P-values. (2) To dig deeper, understand why these methods…
Marc YR Henrion
bootComb is a package for the statistical computation environment R8 and its source code is written in R. bootComb is available from the Comprehensive R Archive Network ([https://CRAN.R-project.org/package=bootComb]()) and can be installed within R by typing the following at the R console: install.packages(‘bootComb’).…
Christoph Dalitz, Felix Lögler
The m-out-of-n bootstrap is a possible workaround to compute confidence intervals for bootstrap inconsistent estimators, because it works under weaker conditions than the n-out-of-n bootstrap. It has the disadvantage, however, that it requires knowledge of an appropriate scaling factor τn and that the coverage…
Authors not listed
Plastic mechanical recycling is the conventional technological step towards circularity. In such aspects, complex mixtures of polyolefin blends are often fed into mechanical recycling systems, resulting in moulded products with uncertain quality. To add to the difficulty of heterogeneous feedstocks, the testing of…
Tina Nane, Kasper Kooijman
Bootstrap methods are increasingly accepted as one of the common approaches in constructing confidence intervals in bibliometric studies. Typical bootstrap methods assume that the statistical population is infinite. When the statistical population is finite, a correction needs to be applied in computing the estimated…
Conrad Hübler
A novel application to determine stability constants from supramolecular titration experiments is presented. The focus lies on NMR titration and ITC experiments for pure 1:1 systems, as well as mixed 2:1/1:1, 1:1/1:2 and 2:1/1:1/1:2 systems. SupraFit provides global and local fitting and a global search tool.…
Stijn Hawinkel, Olivier Thas, Steven Maere
The winner’s curse is a form of selection bias that arises when estimates are obtained for a large number of features, but only a subset of most extreme estimates is reported. It occurs in large scale significance testing as well as in rank-based selection, and imperils reproducibility of findings and follow-up study…
Vincent Dufour-Decieux, Brandi Ransom, Rodrigo Freitas, Jose Blanchet + 1 more
Molecular Dynamics (MD) simulations are a key tool to understand the mechanism of complex chemical system and observe their outcomes in different conditions. However, such simulations are computationally expensive, which limits their timescales to the nanoseconds. This limitation is inconsequential at high…
Nicolas Christou, Ivo D. Dinov, Alejandro Raul Hernandez Montoya
Many scientific investigations depend on obtaining data-driven, accurate, robust and computationally-tractable parameter estimates. In the face of unavoidable intrinsic variability, there are different algorithmic approaches, prior assumptions and fundamental principles for computing point and interval estimates.…
D. Samuel Schwarzkopf
The problems with classical frequentist statistics are well established, yet the enthusiasm of researchers to adopt alternatives like Bayesian inference remains modest. Here I present the bootstrapped evidence test, an objective resampling procedure that takes the precision with which both the experimental and null…
James D. Boyko, Brian C. O’Meara
It is standard statistical practice to provide measures of uncertainty around parameter estimates. Unfortunately, this very basic and necessary enterprise is often absent in macroevolutionary studies. dentist is an R package allows an estimate of confidence intervals around parameter estimates without an analytic…
Carlos Hernandez-Suarez, Jorge Rabinovich
By quantifying key life history parameters in populations, such as growth rate, longevity, and generation time, researchers and administrators can obtain valuable insights into population dynamics. Although point estimates of demographic parameters have been employed since the inception of demography as a scientific…
Authors not listed
The rigorous design of adsorption-based separation processes, such as Pressure Swing Adsorption (PSA) and Temperature Swing Adsorption (TSA), is fundamentally dependent on the accuracy of the underlying mathematical models describing equilibrium isotherms and transport kinetics. However, the current state of the art is…
Paul D.P. Pharoah, Michelle R. Jones, Siddartha Kar
Competing interests: All authors have completed theunified competing interest form and declare: no support from any organisation for the submitted work; no financial relationships with any organisations that might have an interest in the submitted work in the previous three years, no other relationships or activities…
Maria H. Rasmussen, Chenru Duan, Heather J. Kulik, Jan Halborg Jensen
With the increasingly more important role of machine learning (ML) models in chemical research, the need for putting a level of confidence to the model predictions naturally arises. Several methods for obtaining uncertainty estimates have been proposed in recent years but consensus on the evaluation of these have yet…