28 papers · ranked by Valyu relevance
Himel Mallick, Ali Rahnavard, Lauren J. McIver, Siyuan Ma + 17 more
'Yancong Zhang' 'Long H. Nguyen' 'Timothy L. Tickle' 'George Weingart' 'Boyu Ren' 'Emma H. Schwager' 'Suvo Chatterjee' 'Kelsey N. Thompson' 'Jeremy E. Wilkinson' 'Ayshwarya Subramanian' 'Yiren Lu' 'Levi Waldron' 'Joseph N. Paulson' 'Eric A. Franzosa' 'Hector Corrada Bravo' 'Curtis Huttenhower' 'Luis Pedro Coelho'] It…
Amira Ibrahim El-Desokey
In this paper, I outline several conceptual and methodological issues related to modeling individual and group processes embedded in clustered/hierarchical data structures. We position multilevel modeling techniques within a broader set of univariate and multivariate methods commonly used to study different types of…
Ellen F. Mosleth, Kristian Hovde Liland
Modern analysis technologies output large amounts of multivariate data. The data may come from an experimental design or from other collected observations. We here present a flexible tool, called General Effect Modelling (GEM), for the analysis of any type of multivariate data influenced by one or more qualitative…
Willi Sauerbrei, Edwin Kipruto, James Balmford
Background The multivariable fractional polynomial (MFP) approach combines variable selection using backward elimination with a function selection procedure (FSP) for fractional polynomial (FP) functions. It is a relatively simple approach which can be easily understood without advanced training in statistical…
Shuichi Kawano, Toshikazu Fukushima, Junichi Nakagawa, Mamoru Oshiki
The multivariate regression model basically offers the analysis of a single dataset with multiple responses. However, such a single-dataset analysis often leads to unsatisfactory results. Integrative analysis is an effective method to pool useful information from multiple independent datasets and provides better…
José Camacho, Jokin Ezenarro, Daniel Schorn-García, Johan A. Westerhuis
ANOVA Simultaneous Component Analysis (ASCA) is the current state-of-theart chemometric tool for analyzing and interpreting high-dimensional experimental data from a Design of Experiment (DoE). Being a multivariate extension of the ANOVA, ASCA makes a perfect tandem with DoE. This tutorial review recommends best…
Noah Lorincz-Comi, Yihe Yang, Gen Li, Xiaofeng Zhu
Mendelian randomization (MR) is an instrumental variable approach used to infer causal relationships between exposures and outcomes and can apply to summary data from genome-wide association studies (GWAS). Since GWAS summary statistics are subject to estimation errors, most existing MR approaches suffer from…
Miriam Hattle, Danielle L. Burke, Thomas Trikalinos, Christopher H. Schmid + 3 more
'Christopher H. Schmid' 'Yong Chen' 'Dan Jackson' 'Richard D. Riley'] Objectives Multivariate meta-analysis allows the joint synthesis of multiple outcomes accounting for their correlation. This enables borrowing of strength (BoS) across outcomes, which may lead to greater efficiency and even different conclusions…
Hélio Amante Miot
Since all four analytical approaches are absolutely correct and justifiable, it should be remembered that each may lead to different conclusions with respect to the same study. It is therefore the researcher’s prerogative to define, a priori, which approach will be taken, while the analytical techniques, the…
Paolo Girardi, Anna Vesely, Daniël Lakens, Gianmarco Altoè + 3 more
'Massimiliano Pastore' 'Antonio Calcagnì' 'Livio Finos'] When analyzing data researchers make some decisions that are either arbitrary, based on subjective beliefs about the data generating process, or for which equally justifiable alternative choices could have been made. This wide range of data-analytic choices can…
Anita Brobbey, Samuel Wiebe, Alberto Nettel-Aguirre, Colin Bruce Josephson + 3 more
generalized estimation equations Authors: ['Anita Brobbey' 'Samuel Wiebe' 'Alberto Nettel-Aguirre' 'Colin Bruce Josephson' 'Tyler Williamson' 'Lisa M Lix' 'Tolulope T. Sajobi'] Discriminant analysis procedures that assume parsimonious covariance and/or means structures have been proposed for distinguishing between two…
Alexander von Eye, Wolfgang Wiedermann
Unless very large samples are available, the number of variables and variable categories that can be simultaneously used in categorical data analysis is small when models are estimated. In this article, an approach is proposed that can help remedy this problem. Specifically, it is proposed to perform, in a first step…
Mark de Rooij, Ligaya Breemer, Dion Woestenburg, Frank Busing
We present a multidimensional data analysis framework for the analysis of ordinal response variables. Underlying the ordinal variables, we assume a continuous latent variable, leading to cumulative logit models. The framework includes unsupervised methods, when no predictor variables are available, and supervised…
Cattram Nguyen, Katherine J. Lee, Ian R. White, Stef van Buuren + 1 more
imputation: a tutorial Authors: ['Cattram Nguyen' 'Katherine J. Lee' 'Ian R. White' 'Stef van Buuren' 'Margarita Moreno‐Betancur'] Multiple imputation is a popular method for handling missing data, with fully conditional specification (FCS) being one of the predominant imputation approaches for multivariable…
Jon Ahlinder, David Hall, Mari Suontama, Mikko J Sillanpää
A cornerstone in breeding and population genetics is the genetic evaluation procedure, needed to make important decisions on population management. Multivariate mixed model analysis, in which many traits is considered jointly, utilizes genetic and environmental correlations between traits to improve the accuracy.…
Authors not listed
The analysis of nonadiabatic molecular dynamics (NAMD) data presents significant challenges due to its high dimensionality and complexity. To address these issues, we introduce ULaMDyn, a Python-based, open-source package designed to automate the unsupervised analysis of large datasets generated by NAMD simulations.…
Authors not listed
Decades of extensive research have proved that β-amyloid (Aβ) peptides and their aggregation, inducing oxidative stress in the brain, play a key role in Alzheimer’s disease (AD) development. Moreover, Aβ peptides bind to Cu(II) ions, and the resulting complexes accelerate the aggregation process while promoting the…
Christoph Sperber
For years, dissociation studies on neurological single cases with brain lesions were the dominant method to infer fundamental cognitive functions in neuropsychology. In contrast, the association between deficits was considered to be of less epistemological value and even misleading. Still, principal component analysis…
Ludwig A. Hothorn
In bio-medical studies, the p-values of the F-tests in ANOVA are usually interpreted independently as measures of the significance of the associated factors. This ’hidden multiplicity’ effect increases the false positive rate. Therefore, Cramer et al. (2016) proposed the Bonferroni adjustment of the p-values to control…
Calvin Guan, Ashis Gangopadhyay
Although there are many methods available in the literature to compare the covariance structures of two populations, few are suitable for clinical application due to the inability to account for covariate(s) that affect the dependence structure of the variables being investigated. A common method is to adjust the…
Christian Acal, Ana M. Aguilera
The methodological contribution in this paper is motivated by biomechanical studies where data characterizing human movement are waveform curves representing joint measures such as flexion angles, velocity, acceleration, and so on. In many cases the aim consists of detecting differences in gait patterns when several…
Authors not listed
The SCF part of the HF-SCF method is responsible for finding the ground state as the global minimum of the one-determinant approximation of the electronic energy, which is a 4th order multivariable polynomial of the LCAO coefficients and Lagrange multipliers. In this work we replace this SCF part with algebraic…
S. Ghazaleh Dashti, Katherine J. Lee, J. A. Simpson, John B. Carlin + 1 more
S. Ghazaleh Dashti1,2, Katherine J. Lee1,2, Julie A. Simpson3,4, John B. Carlin1,2,3, Margarita Moreno-Betancur1,2 1 Department of Pediatrics, University of Melbourne, Melbourne, Victoria, Australia 2 Clinical Epidemiology and Biostatistics Unit, Murdoch Children's Research Institute, Melbourne, Victoria, Australia 3…
Pablo Quijano Velasco, Kedar Hippalgaonkar, Balamurugan Ramalingam
The discovery of optimal conditions of chemical reactions is a labor-intensive, time-consuming task that requires exploring a high-dimensional parametric space. Historically the optimization of chemical reactions has been performed by manual experimentation guided by human intuition and Design of Experiments where one…
Zinan Lu, Jonathan Anns, Yishan Mai, Rou Zhang + 10 more
Data analysis in experimental science mainly relies on null-hypothesis significance testing, despite its well-known limitations. A powerful alternative is estimation statistics, which focuses on effect-size quantification. However, current estimation tools struggle with the complex, multi-group comparisons common in…
Authors not listed
Deciphering the correct mechanism governing certain phenomenon in polyelectrolyte (PE) brush grafted systems, revealed through atomistic simulations, is an extremely challenging problem. In a recent study, our all-atom molecular dynamics (MD) simulations revealed a non-linearly large electroosmotic flow (in the…
Andrew McCluskey
The use of mathematical transformations to reduce non-linear functions to linear problems, which can be tackled with analytical linear regression, is commonplace in the chemistry curriculum. The linearization procedure, however, assumes an incorrect statistical model for real experimental data; leading to biased…
Authors not listed
Background: Pharmaceutical batch scheduling in multi-reactor configurations presents complex optimization challenges under operational uncertainty, yet limited research addresses how parallel processing capacity affects heuristic performance and predictive modeling. Objectives: This study investigated scheduling…