24 papers · ranked by Valyu relevance
Bodo Winter
Linear models and linear mixed models are an impressively powerful and flexible tool for understanding the world. This tutorial is a decidedly conceptual introduction to this class of models. The focus is on understanding what these models are doing … and then we'll spend most of the time applying this understanding…
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…
Joakim Nyberg, E. Niclas Jonsson, Mats O. Karlsson, Jonas Häggström
Two full model approaches was compared with respect to their ability to handle missing covariate information. The reference data analysis approach was the full model method in which the covariate effects are estimated conventionally using fixed effects, and missing covariate data is imputed with the median of 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…
Jessica I. Murphy, Nicholas E. Weaver, Audrey E. Hendricks
Longitudinal mouse models are commonly used to study 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…
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.…
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…
G. A. Meshcheryakov, Anna A. Igolkina, Maria Samsonova
Structural Equation Modeling (SEM) is an umbrella term that includes numerous multivariate statistical techniques that are employed throughout a plethora of research areas, ranging from social to natural sciences. Until recently, SEM software was either commercial or restricted to niche languages, and the lack of SEM…
Johannes Oberpriller, Melina de Souza Leite, Maximilian Pichler
Biological data are often intrinsically hierarchical. Due to their ability to account for such dependencies, mixed-effects models have become a common analysis technique in ecology and evolution. While many questions around their theoretical foundations and practical applications are solved, one fundamental question is…
Eldin Dzubur, Aditya Ponnada, Rachel Nordgren, Chih-Hsiang Yang + 3 more
'Stephen Intille' 'Genevieve Dunton' 'Donald Hedeker'] The use of intensive sampling methods, such as ecological momentary assessment (EMA), is increasingly prominent in medical research. However, inferences from such data are often limited to the subject-specific mean of the outcome and between-subject variance (i.e.…
Ashenfai A Yirga, Sileshi F Melesse, Henry G Mwambi, Dawit G Ayele
Background This study aims to make use of a longitudinal data modelling approach to analyze data on the number of CD4+cell counts measured repeatedly in HIV-1 Subtype C infected women enrolled in the Acute Infection Study of the Centre for the AIDS Programme of Research in South Africa. Methodology This study uses data…
Dylan G.E. Gomes
As (generalized) linear mixed-effects models (GLMMs) have become a widespread tool in ecology, the need to guide the use of such tools is increasingly important. One common ‘rule of thumb’ is that one needs at least five levels of a random effect. Having such few levels makes the estimation of the variance of random…
Martin A. Stoffel, Shinichi Nakagawa, Holger Schielzeth
The coefficient of determination R^2^ quantifies the amount of variance explained by regression coefficients in a linear model. It can be seen as the fixed-effects complement to the repeatability R (intra-class correlation) for the variance explained by random effects and thus as a tool for variance decomposition. The…
Oluwatobi Blessing Ojo, Siaka Lougue, Woldegebriel Assefa Woldegerima, Rongling Wu
'Rongling Wu'] TB is rated as one of the world’s deadliest diseases and South Africa ranks 9th out of the 22 countries with hardest hit of TB. Although many pieces of research have been carried out on this subject, this paper steps further by inculcating past knowledge into the model, using Bayesian approach with…
Klaus K. Holst, Esben Budtz‐Jørgensen
An R package for specifying and estimating linear latent variable models is presented. The philosophy of the implementation is to separate the model specification from the actual data, which leads to a dynamic and easy way of modeling complex hierarchical structures. Several advanced features are implemented including…
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…
Joop J. Hox, Mirjam Moerbeek, Anouck Kluytmans, Rens van de Schoot
Cluster randomized trials assess the effect of an intervention that is carried out at the group or cluster level. Ajzen's theory of planned behavior is often used to model the effect of the intervention as an indirect effect mediated in turn by attitude, norms and behavioral intention. Structural equation modeling…
Steven Geinitz, Reinhard Furrer
Assessing variability according to distinct factors in data is a fundamental technique of statistics. The method commonly regarded to as analysis of variance (ANOVA) is, however, typically confined to the case where all levels of a factor are present in the data (i.e. the population of factor levels has been…
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…
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.…
Jeffrey A. Walker
Model-averaged partial regression coefficients have been criticized for averaging over a set of models with coefficients that have different meanings from model to model. This criticism arises because statisticians since Fisher believe that the meaning of a coefficient in a regression model arises from probabilistic…
Authors not listed
Terminally labeled DNA oligonucleotides have wide applications in modern biology and biotechnological applications. It has been observed that the fluorescent intensity of light released from these fluorescent labels is heavily influenced by the terminal sequence of nucleotides. Recent studies have assayed and published…
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…