library(gemtc)library(rjags)library(dmetar)data(TherapyFormatsGeMTC)head(TherapyFormatsGeMTC$data)TherapyFormatsGeMTC$treat.codes network<-mtc.network(data.re=TherapyFormatsGeMTC$data,treatments=TherapyFormatsGeMTC$treat.codes)model<-mtc.model(network,likelihood="normal",link="identity",linearModel="random...
A Bayesian model-averaged meta-analysis of the power pose effect with informed and default priors: The case of felt power.Gronau, Q F, van Erp, S, Heck, D W, Cesario, J, Jonas, K J and Wagenmakers, E-J 2017 "A bayesian model-averaged meta-analysis of the power pose effect with...
The forest plot is quite similar to the one based on the mixed effects model, though as predicted, the 95% CI is considerably wider: As a comparison, here is the plot from the mixed effects model estimated using thenlmepackage in the previous post. The bootstrapped estimates of uncertainty ...
AnkeMeyer-Baese,VolkerSchmid, inPattern Recognition and Signal Analysis in Medical Imaging (Second Edition), 2014 6.6Bayesian Networks Bayesian networksare frequently used as classification tools. A Bayesian network is a graphical model based on probabilistic beliefs. A Bayesian network consists of stoch...
The present Bayesian network meta-analysis compared different types of polyethylene liners in total hip arthroplasty (THA) in terms of wear penetration (mm/year) and rate of revision. The type of liners compared were the crosslinked ultra-high molecular
Analyses were performed with comprehensive meta-analysis soft- ware (version 2.0, National Institute of Health)22. Second, we did network meta-analyses or mixed treatment comparisons for each outcome. Using a Bayesian hierarchical random-effect model with noninformative prior hypothesis, all direct ...
The bar plots in the last column of Fig. 4 represent the model’s predictions when no findings are inserted in the network. These distributions represent ES supply and associated uncertainties for a random location in Flanders and can be referred to as a the prior probability distributions. The...
1999. Learning Bayesian decision analysis by doing: lessons from environmental and natural resources management. Ecologi- cal Modelling 119: 177–195. Wang QJ, Robertson DE, Haines CL. 2009. A Bayesian network approach to knowledge integration and representation of farm irrigation: 1. Model ...
we have chosen to perform a Bayesian network (BN) analysis instead of a partial correlation network analysis or Markov random field analysis18. The final BN, the found dependencies and predictions for hypothetical patients were compared to expert opinion to assess the potential of the model for fu...
Bayesian hierarchical modelMAP estimationmeta analysisrelevance vector machineshrinkageMany biomedical applications are concerned with the problem of selecting important predictors from a high-dimensional set of candidates, with the gene expression data as one example. Due to the fact that the sample size...