25 papers · ranked by Valyu relevance
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…
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…
Joël L. Horowitz
The bootstrap is a method for estimating the distribution of an estimator or test statistic by resampling one's data or a model estimated from the data. Under conditions that hold in a wide variety of econometric applications, the bootstrap provides approximations to distributions of statistics, coverage probabilities…
Aiora Zabala, Unai Pascual, Yinglin Xia
Q is a semi-qualitative methodology to identify typologies of perspectives. It is appropriate to address questions concerning diverse viewpoints, plurality of discourses, or participation processes across disciplines. Perspectives are interpreted based on rankings of a set of statements. These rankings are analysed…
Fumikazu Miwakeichi, Andreas Galka, Hector Zenil, Jiang Zhang + 1 more
'Peng Cui'] In this study, we present a thorough comparison of the performance of four different bootstrap methods for assessing the significance of causal analysis in time series data. For this purpose, multivariate simulated data are generated by a linear feedback system. The methods investigated are uncorrelated…
Thomas Pitschel
An algorithm is described that enables efficient deterministic approximate computation of the bootstrap distribution for any linear bootstrap method T ∗ n , alleviating the need for repeated resampling from observations (resp. input-derived data). In essence, the algorithm computes the distribution function from a…
Shuting Liao, Kantharakorn Macharoen, Karen A. McDonald, Somen Nandi + 1 more
We propose a method for analyzing the variability in smooth, possibly nonlinear, functionals associated with a set of product production trajectories measured under different experimental conditions. The key challenge is to make meaningful inference on these parameters across different experimental conditions when only…
Jared Clark, Richard L. Warr
Bootstrapping was designed to randomly resample data from a fixed sample using Monte Carlo techniques. However, the original sample itself defines a discrete distribution. Convolutional methods are well suited for discrete distributions, and we show the advantages of utilizing these techniques for bootstrapping. The…
Varun Saravanan, Gordon J. Berman, Samuel J. Sober
A common feature in many neuroscience datasets is the presence of hierarchical data structures, most commonly recording the activity of multiple neurons in multiple animals across multiple trials. Accordingly, the measurements constituting the dataset are not independent, even though the traditional statistical…
Vladimir Makarenkov, Alix Boc, Jingxin Xie, Pedro Peres-Neto + 2 more
'François-Joseph Lapointe' 'Pierre Legendre'] Background Non-parametric bootstrapping is a widely-used statistical procedure for assessing confidence of model parameters based on the empirical distribution of the observed data [1] and, as such, it has become a common method for assessing tree confidence in…
Zhonglei Wang, Jae Kwang Kim, Liuhua Peng
Bootstrap is a useful tool for making statistical inference, but it may provide erroneous results under complex survey sampling. Most studies about bootstrap-based inference are developed under simple random sampling and stratified random sampling. In this paper, we propose a unified bootstrap method applicable to some…
F. Lemoine, J.-B. Domelevo Entfellner, E. Wilkinson, T. De Oliveira + 1 more
Felsenstein’s article describing the application of the bootstrap to evolutionary trees, is one of the most cited papers of all time. That statistical method, based on resampling and replications, is used extensively to assess the robustness of phylogenetic inferences. However, increasing numbers of sequences are now…
Asep Setiaji, Takuro Oikawa
Objective The objective of this study was to determine the best approach for handling missing records of first to successful insemination (FS) in Japanese Black heifers. Methods Of a total of 2,367 records of heifers born between 2003 and 2015 used, 206 (8.7%) of open heifers were missing. Four penalty methods based on…
Guangming Li, Peida Zhan
Based on the standard of comparison and decision rules, the performance of these methods under different data conditions is graded and showed in [pone.0288069.t005], with the "+" symbol meaning accurate and the "-" symbol meaning inaccurate. As shown in [pone.0288069.t005], the traditional method, jackknife method and…
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…
Behnam Yousefimehr, Mehdi Ghatee, Mohammad Amin Seifi, Javad Fazli + 9 more
'Sajed Tavakoli' 'Zahra Rafei' 'Shervin Ghaffari' 'Abolfazl Nikahd' 'Mahdi Razi Gandomani' 'Alireza Orouji' 'Ramtin Mahmoudi Kashani' 'Sarina Heshmati' 'Negin Sadat Mousavi'] Imbalanced data poses a significant obstacle in machine learning, as an unequal distribution of class labels often results in skewed predictions…
Rory M. Crean, Joanna S. G. Slusky, Peter M. Kasson, Shina Caroline Lynn Kamerlin
Simulation datasets of proteins (e.g., those generated by molecular dynamics simulations) are filled with information about how the non-covalent interaction network within a protein regulates the conformation and thus function of said protein. Most proteins contain thousands of non-covalent interactions, with most of…
Grasiela Casas, Vinicius A.G. Bastazini, Vanderlei J. Debastiani, Valério D. Pillar
Sampling the full diversity of interactions in an ecological community is a highly intensive effort. Recent studies have demonstrated that many network metrics are sensitive to both sampling effort and network size. Here, we develop a statistical framework, based on bootstrap resampling, that aims to assess sampling…
Christian Thiele, Gerrit Hirschfeld
"Optimal cutpoints" for binary classification tasks are often established by testing which cutpoint yields the best discrimination, for example the Youden index, in a specific sample. This results in "optimal" cutpoints that are highly variable and systematically overestimate the out-of-sample performance. To address…
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…
Guido Melchior
This paper aims at resolving a puzzle about the persuasiveness of bootstrapping. On the one hand, bootstrapping is not a persuasive method of settling questions about the reliability of a source. On the other hand, our beliefs that our sense apparatus is reliable is based on other empirically formed beliefs, that is…
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…
Authors not listed
Solubility is critical in drug discovery and development, as it significantly influences a medication's bioavailability and therapeutic efficacy. Understanding solubility at the early stages of drug discovery is essential for minimizing resource consumption and enhancing the likelihood of clinical success via…
Robert Arbon, Yanchen Zhu, Antonia S. J. S. Mey
Markov state models (MSM) are a popular statistical method for analyzing the conformational dynamics of proteins, including protein folding. With all statistical and machine learning (ML) models choices must be made about the modeling pipeline that cannot be directly learned from the data. These choices, or…
Surl-Hee Ahn, Anupam Ojha, Rommie Amaro, James McCammon
Gaussian accelerated molecular dynamics (GaMD) is a well-established enhanced sampling method for molecular dynamics (MD) simulations that effectively samples the potential energy landscape of the system by adding a boost potential, which smoothens the surface and lowers energy barriers between states. Although…