Results 21 to 30 of about 1,397,188 (342)

Ignoring uncertainty in predictor variables leads to false confidence in results: a case study of duck habitat use

open access: yesEcosphere, 2020
An assumption of most regression analyses is that independent variables are measured without error. However, in ecological studies it is common to use independent variables that are derived from samples and therefore contain some uncertainty. For example,
Adam C. Behney
doaj   +1 more source

Musical Expectancy. Bridging Music Theory, Cognitive and Computational Approaches [PDF]

open access: yesZeitschrift der Gesellschaft für Musiktheorie, 2013
This article contributes to an interdisciplinary discussion of ways in which music-theoretical, cognitive, and computational accounts of musical expectancy may be bridged.
Martin Rohrmeier
doaj   +1 more source

Influence of Sociodemographic, Health-Related, and Behavioral Factors on Food Guidelines Compliance in Older Adults: A Hierarchical Approach from the Chilean National Health Survey 2016–17 Data

open access: yesGeriatrics, 2022
Dietary habits are determinants in the development of a range of conditions and age-related diseases. We explored the associations of sociodemographic, health-related indicators, and health behavioral factors on dietary guideline compliance in elderly ...
Leticia de Albuquerque-Araújo   +3 more
doaj   +1 more source

Hierarchical Models for Independence Structures of Networks [PDF]

open access: yes, 2019
We introduce a new family of network models, called hierarchical network models, that allow us to represent in an explicit manner the stochastic dependence among the dyads (random ties) of the network.
Bishop Y. M.   +7 more
core   +2 more sources

Hierarchical Configuration Model [PDF]

open access: yesInternet Mathematics, 2017
23 pages, 11 ...
van der Hofstad, R.   +2 more
openaire   +3 more sources

A practical guide to understanding and validating complex models using data simulations

open access: yesMethods in Ecology and Evolution, 2023
Biologists routinely fit novel and complex statistical models to push the limits of our understanding. Examples include, but are not limited to, flexible Bayesian approaches (e.g. BUGS, stan), frequentist and likelihood‐based approaches (e.g.
Graziella V. DiRenzo   +2 more
doaj   +1 more source

Dissecting magnetar variability with Bayesian hierarchical models [PDF]

open access: yes, 2015
Neutron stars are a prime laboratory for testing physical processes under conditions of strong gravity, high density, and extreme magnetic fields. Among the zoo of neutron star phenomena, magnetars stand out for their bursting behaviour, ranging from ...
Brewer, B. J.   +9 more
core   +3 more sources

A hierarchical model for ageing [PDF]

open access: yesJournal of Physics A: Mathematical and General, 1997
We present a one dimensional model for diffusion on a hierarchical tree structure. It is shown that this model exhibits aging phenomena although no disorder is present. The origin of aging in this model is therefore the hierarchical structure of phase space.
Geppert, U.   +2 more
openaire   +4 more sources

Applying SEM, Exploratory SEM, and Bayesian SEM to Personality Assessments

open access: yesPsych
Despite the importance of demonstrating and evaluating how structural equation modeling (SEM), exploratory structural equation modeling (ESEM), and Bayesian structural equation modeling (BSEM) work simultaneously, research comparing these analytic ...
Hyeri Hong   +2 more
doaj   +1 more source

Fixed or random? On the reliability of mixed‐effects models for a small number of levels in grouping variables

open access: yesEcology and Evolution, 2022
Biological data are often intrinsically hierarchical (e.g., species from different genera, plants within different mountain regions), which made mixed‐effects models a common analysis tool in ecology and evolution because they can account for the non ...
Johannes Oberpriller   +2 more
doaj   +1 more source

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