Applied Bayesian Modelling

By P. Congdon. 2003

563 citations recorded by the source corpus.

Subfields: Modeling and Simulation, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/f1e561012bf64ced100542a3a61b8a5a6caca0a6

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Citations in the corpus

Cancer survivors and unemployment: a meta-analysis and meta-regression. (2009, background): “Bradley et al30 2006 (United States) Cervical 54 (100) 55 (12) 11 (6-20) Sex Hospital-based cross-sectional survey/non–cancer patients survey”
General quantitative genetic methods for comparative biology: phylogenies, taxonomies and multi‐trait models for continuous and categorical characters (2010, methodology): “Numerous methods have been developed to detect and to correct for publication bias, but there appears to be no consensus on a general method (Smith et al., 2000; Congdon, 2003; Rothstein et al., 2005).”
Changing philosophies and tools for statistical inferences in behavioral ecology (2009, methodology): “Readers are recommended to consult with accessible introductory books (Gelman and Hill 2007; McCarthy 2007) on Bayesian statistics or more thorough reviews (Gelman et al. 1995; Gill 2002; Congdon 2003, 2005, 2006).”
A Moran coefficient-based mixed effects approach to investigate spatially varying relationships (2016, methodology): “2 Congdon (2014) publishes an R code of an INLA to estimate a conditional autoregressive model-based SVC model (see Gamerman et al., 2003). from a comparative Monte Carlo simulation experiment, and section 7 uses our model in 43 a hedonic analysis.”
Bayesian analysis of linear dominance hierarchies (2005, methodology): “Bayesian inference combines (1) a likelihood function with (2) prior probability distributions for each model parameter to produce (3) posterior probability distributions for quantities of interest (Congdon 2003; Gelman et al. 2004).”
Bayesian hypothesis testing for psychologists: a tutorial on the Savage-Dickey method. (2010, unknown): “More detailed information can be found in Bayesian articles and books that discuss philosophical foundations (Lindley, 2000; O’Hagan & Forster, 2004), computational innovations (Gamerman & Lopes, 2006), and practical contributions (Congdon, 2003; Ntzoufras, 2009).”
Model Selection Methods for Mixture Dichotomous IRT Models (2009, methodology): “In addition, Congdon (2003) described versions of AIC and BIC for use with MCMC estimation.”
The Rasch Testlet Model (2005, background): “This tendency should be explicitly acknowledged and avoided (Congdon, 2003; Gelman, Carlin, Stern, & Rubin, 2003; Lee, 1989; Punt & Hilborn, 1997).”
Assessing Evidence Inconsistency in Mixed Treatment Comparisons (2006, background): “The goodness-of-fit of a model to data can be measured by the sum of residual deviance (McCullagh and Nelder 1989; Congdon 2003).”
Invasive plants and their ecological strategies: prediction and explanation of woody plant invasion in New England (2007, methodology): “By using a hierarchical Bayesian model, instead of assuming complete independence among growth forms on the one hand, and identical response on the other, we allowed the data to inform how closely the growth forms covaried in their trait associations (Congdon, 2003).”
A New Robust Regression Model for Proportions (2012, background): “However, in some empirical situations, the sample size may be small and in such cases Bayesian inference seems to be more suitable if previous information about the parameters is available, see Congdon (2003) and Gelman et al. (2003). In this section we propose a Bayesian approach.”