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   Articles with "hierarchical models" as a keyword



Prior choice and data requirements of Bayesian multivariate hierarchical models fit to tag‐recovery data: The need for power analyses

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recommendations! Published in 2023 at "Ecology and Evolution"

DOI: 10.1002/ece3.9847

Abstract: Abstract Recent empirical studies have quantified correlation between survival and recovery by estimating these parameters as correlated random effects with hierarchical Bayesian multivariate models fit to tag‐recovery data. In these applications, increasingly negative correlation between… read more here.

Keywords: recovery data; hierarchical models; power; tag recovery ... See more keywords

Comparing hierarchical models via the marginalized deviance information criterion.

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recommendations! Published in 2018 at "Statistics in medicine"

DOI: 10.1002/sim.7649

Abstract: Hierarchical models are extensively used in pharmacokinetics and longitudinal studies. When the estimation is performed from a Bayesian approach, model comparison is often based on the deviance information criterion (DIC). In hierarchical models with latent… read more here.

Keywords: hierarchical models; information criterion; deviance information; criterion ... See more keywords

Bayesian Hierarchical Models as Tools to Evaluate the Association Between Groundwater Quality and the Occurrence of Type 2 Diabetes in Rural Saskatchewan, Canada

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recommendations! Published in 2019 at "Archives of Environmental Contamination and Toxicology"

DOI: 10.1007/s00244-018-00588-4

Abstract: There is growing interest in the role of environmental exposures in the development of diabetes. Previous studies in rural Saskatchewan have raised concerns over drinking water contaminants, including arsenic, which has been identified as a… read more here.

Keywords: hierarchical models; water; bayesian hierarchical; health standards ... See more keywords
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Normalization and pooling in hierarchical models of natural images

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recommendations! Published in 2019 at "Current Opinion in Neurobiology"

DOI: 10.1016/j.conb.2019.01.008

Abstract: Divisive normalization and subunit pooling are two canonical classes of computation that have become widely used in descriptive (what) models of visual cortical processing. Normative (why) models from natural image statistics can help constrain the… read more here.

Keywords: hierarchical models; normalization pooling; image statistics; pooling hierarchical ... See more keywords

Natural element approximation of hierarchical models of plate-like elastic structures

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recommendations! Published in 2020 at "Finite Elements in Analysis and Design"

DOI: 10.1016/j.finel.2020.103439

Abstract: Abstract Almost all the mesh-free methods are restricted to 2-D problems owing to the difficulty in generating 3-D grids. One effective way to overcome this limitation is to utilize the concept of hierarchical modeling for… read more here.

Keywords: hierarchical models; elastic structures; natural element; plate like ... See more keywords
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Normal Binary Hierarchical Models

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recommendations! Published in 2017 at "Experimental Mathematics"

DOI: 10.1080/10586458.2016.1142911

Abstract: ABSTRACT Each simplicial complex and integer vector yields a vector configuration whose combinatorial properties are important for the analysis of contingency tables. We study the normality of these vector configurations including a description of operations… read more here.

Keywords: binary hierarchical; vector; hierarchical models; normal binary ... See more keywords

Generating Independent Replicates Directly from the Posterior Distribution for a Class of Spatial Hierarchical Models

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recommendations! Published in 2024 at "Journal of Computational and Graphical Statistics"

DOI: 10.1080/10618600.2024.2365728

Abstract: Abstract Markov chain Monte Carlo (MCMC) allows one to generate dependent replicates from a posterior distribution for effectively any Bayesian hierarchical model. However, MCMC can produce a significant computational burden. This motivates us to consider… read more here.

Keywords: distribution; posterior distribution; replicates directly; independent replicates ... See more keywords

Obtaining population-based estimates for survey data using Bayesian hierarchical models with Poststratification.

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recommendations! Published in 2025 at "American journal of epidemiology"

DOI: 10.1093/aje/kwaf209

Abstract: For large-scale surveys such as the National Health and Aging Trends Study (NHATS), investigators may wish to combine data from two (or more) cohorts in a single analysis to obtain larger sample sizes. Unfortunately, it… read more here.

Keywords: based estimates; bayesian hierarchical; population based; models poststratification ... See more keywords

Nonparametric scanning tests of homogeneity for hierarchical models with continuous covariates.

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recommendations! Published in 2022 at "Biometrics"

DOI: 10.1111/biom.13801

Abstract: In many applications of hierarchical models, there is often interest in evaluating the inherent heterogeneity in view of observed data. When the underlying hypothesis involves parameters resting on the boundary of their support space such… read more here.

Keywords: scanning tests; heterogeneity; nonparametric scanning; hierarchical models ... See more keywords

Scalable Target Marketing: Distributed Markov Chain Monte Carlo for Bayesian Hierarchical Models

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recommendations! Published in 2020 at "Journal of Marketing Research"

DOI: 10.1177/0022243720952410

Abstract: Many problems in marketing and economics require firms to make targeted consumer-specific decisions, but current estimation methods are not designed to scale to the size of modern data sets. In this article, the authors propose… read more here.

Keywords: hierarchical models; monte carlo; markov chain; distributed markov ... See more keywords

Predicting Verbal Learning and Memory Assessments of Older Adults Using Bayesian Hierarchical Models

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recommendations! Published in 2022 at "Frontiers in Psychology"

DOI: 10.3389/fpsyg.2022.855379

Abstract: Verbal learning and memory summaries of older adults have usually been used to describe neuropsychiatric complaints. Bayesian hierarchical models are modern and appropriate approaches for predicting repeated measures data where information exchangeability is considered and… read more here.

Keywords: hierarchical models; bayesian hierarchical; memory; psychology ... See more keywords