23 papers · ranked by Valyu relevance
Keith R. Lohse, Allan J. Kozlowski, Michael Strube
Mixed-effect models are flexible tools for researchers in a myriad of fields, but that flexibility comes at the cost of complexity and if users are not careful in how their model is specified, they could be making faulty inferences from their data. We argue that there is significant confusion around appropriate random…
Dylan G.E. Gomes, Diogo Provete
As linear mixed-effects models (LMMs) have become a widespread tool in ecology, the need to guide the use of such tools is increasingly important. One common guideline is that one needs at least five levels of the grouping variable associated with a random effect. Having so few levels makes the estimation of the…
Jessica I. Murphy, Nicholas E. Weaver, Audrey E. Hendricks
Longitudinal studies are commonly used to examine possible causal factors associated with human health and disease. However, the statistical models, such as two-way ANOVA, often applied in these studies do not appropriately model the experimental design, resulting in biased and imprecise results. Here, we describe the…
Lutfiyya N. Muhammad
Introduction A study design with repeated measures data occurs when each experimental unit has multiple dependent variable observations collected at several time points. Often longitudinal data (1, 2) are used interchangeably to describe repeated measures data. This study design also includes two or more experimental…
Hans-Peter Piepho
Finlay-Wilkinson regression is one of the most popular methods for analysing genotype-environment interaction in series of plant breeding and variety trials. The method involves a regression on the environmental mean, computed as the average of all genotype means. The environmental mean is an index for the productivity…
Gerhard Tutz
Type and Continuous Dependent Variables Including Variable Selection Authors: ['Gerhard Tutz'] A general random effects model is proposed that allows for continuous as well as discrete distributions of the responses. Responses can be unrestricted continuous, bounded continuous, binary, ordered categorical or given in…
Stefan Konigorski, Mathias Ried‐Larsen, Christopher H. Schmid
Traditionally, studies in experimental physiology have been conducted in small groups of human participants, animal models or cell lines. Identifying optimal study designs that achieve sufficient power for drawing proper statistical inferences to detect group level effects with small sample sizes has been challenging.…
Christopher Schmid, Jiabei Yang
We describe Bayesian models for data from N-of-1 trials, reviewing both the basics of Bayesian inference and applications to data from single trials and collections of trials sharing the same research questions and data structures. Bayesian inference is natural for drawing inferences from N-of-1 trials because it can…
Hongwei Zhao, Joris Mulder
Random effects are the gold standard for capturing structural heterogeneity in data, such as spatial dependencies, individual differences, or temporal dependencies. However, testing for their presence is challenging, as it involves a variance component constrained to be non-negative – a boundary problem. This paper…
Disha Ghandwani, Swarnadip Ghosh, Trevor Hastie, Art B. Owen
The crossed random effects model is widely used, finding applications in various fields such as longitudinal studies, e-commerce, and recommender systems, among others. However, these models encounter scalability challenges, as the computational time for standard algorithms grows superlinearly with the number N of…
Pravesh Parekh, Nadine Parker, Diliana Pecheva, Evgeniia Frei + 22 more
While linear mixed-effects (LME) models are common for analyzing longitudinal data, most users rely on random intercepts or simple stationary covariance, due to unavailability of computationally tractable solutions. Here, we extend the Fast and Efficient Mixed-Effects Algorithm (FEMA) and present FEMA-Long, a…
Soumen Dey, Ehsan M. Moqanaki, Cyril Milleret, Pierre Dupont + 2 more
Spatial capture-recapture (SCR) models are now widely used for estimating density from repeated individual spatial encounters. SCR accounts for the inherent spatial autocorrelation in individual detections by modelling detection probabilities as a function of distance between the detectors and individual activity…
Paulo Pagliari, Fernando Shintate Galindo, Jeffrey Strock, Carl Rosen + 1 more
'Carl Rosen' 'Georgios Koubouris'] Field studies conducted over time to collect any type of plant response to a set of treatments are often not treated as repeated measures data. The most used approaches for statistical analyses of this type of longitudinal data are based on separate analyses such as ANOVA, regression…
Sean C. Anderson, Eric J. Ward, Philina A. English, Lewis A. K. Barnett
Geostatistical data—spatially referenced observations related to some continuous spatial phenomenon— are ubiquitous in ecology and can reveal ecological processes and inform management decisions. However, appropriate models to analyze these data, such as generalized linear mixed effects models (GLMMs) with Gaussian…
Priscilla Balestrucci, Marc O. Ernst, Alessandro Moscatelli
Psychophysical methods are widely used in neuroscience to investigate the quantitative relation between a physical property of the world and its perceptual representation provided by the senses. Recent studies introduced the Generalized Linear Mixed Model (GLMM) to fit the responses of multiple participants in…
Angela Andreella, Livio Finos
Linear mixed models are widely used to analyze non-independent data, but inference for fixed effects can be unreliable under misspecification of the random-effects distribution, inaccurate Fisher information estimation, or convergence failures, leading to a lack of control over false positives. These difficulties are…
C. A. Avellaneda, Oscar O. Melo, N. A. Cruz
In many countries, it is common to apply standardized tests that measure secondary education, which must be taken by all students at the end of grade 11 or ISCED level 3 (International Standard Classification of Education UNESCO (2012); Covacevich et al. (2021)) as a prerequisite to obtaining their degree. The…
Michelle Frankot, Peyton M. Mueller, Michael E. Young, Cole Vonder Haar
Statistical errors in preclinical science are a barrier to reproducibility and translation. For instance, linear models (e.g., ANOVA, linear regression) may be misapplied to data that violate assumptions. In behavioral neuroscience and psychopharmacology, linear models are frequently applied to interdependent or…
Authors not listed
Metastable states and the conformational transitions in between them are key to understanding dynamical behaviour and function of large-scale molecular systems. By combining basic dimensionality reduction techniques with a state-of-the art approximation of the Koopman operator associated to molecular dynamics…
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.…
Moayad Alnammi, Shengchao Liu, Spencer S Ericksen, Gene E Ananiev + 6 more
Traditional small molecule drug discovery is a time consuming and costly endeavor. High-throughput chemical screening can only assess a tiny fraction of drug-like chemical space. The strong predictive power of modern machine learning methods for virtual chemical screening enables training models on known active and…
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…
Devi Ganapathi, Wunmi Akinlemibola, Antonio Baclig, Emily Penn + 1 more
Quinones and hydroquinones are small organic molecules with numerous applications: battery electrolytes, pharmaceuticals, sensors, to name a few. An understanding of their fundamental properties, such as melting points, is essential to incorporate these compounds into relevant technologies. In this study, two different…