In recent years numerous meta-regression models for benefit transfer in the context of environmental quality changes have been proposed by the academic literature and used by government agencies for policy makin
Time to benefit for colorectal cancer screening: survival meta-analysis of flexible sigmoidoscopy trials. BMJ ▶ Vittinghoff E, Glidden DV, Shiboski SC, McCulloch CE (2012). Regression methods in biostatistics: linear, logistic, survival, and repeated measures models. Springer ▶ Wei Y, ...
The proposed meta-regression is formulated by jointly modeling the association parameters and the functional meta-predictors using Dirichlet process (DP) or local DP mixtures. In doing so, the functional meta-predictors are represented parsimoniously by the coefficients of the orthonormal basis. The ...
Strategy We applied bayesian meta-regression methods10 to multiple data sources with the goal of producing estimates of the prevalence and uncertainty interval of visual acuity loss or blindness, stratified by age group, sex, race/ethnicity, and state (50 US states and Washington, DC) for the ...
The deviation of the SUCRAs or P﹕cores from their theoretical values was mostly comparable over the methods, but differed depending on the heterogeneity and the geometry of the investigated network. Multivariate meta‐regression or Bayesian estimation using a half‐normal prior scaled to 0.5 seem ...
Accurate prediction of an individual's phenotype from their DNA sequence is one of the great promises of genomics and precision medicine. We extend a powerful individual-level data Bayesian multiple regression model (BayesR) to one that utilises summary statistics from genome-wide association studies...
The results presented here show that the proposed Bayesian meta-regression approach is feasible and produces plausible results which do not contradict the bulk of evidence regarding the shape of the distribution of average alcohol consumption among drinkers and the variation of consumption patterns with ...
Bayesian model averaging (BMA) Concepts of BMA Usage of BMA BMA versus frequentist model averaging Computational methods for BMA Motivating examples Example 1: BMA linear regression Example 2: BMA for prediction compared with other approaches Example 3: BMA with small sample size and many predictors...
and also for our new semiparametric approach. many of the same sites are identified by both methods, however, our new method performs slightly better than the regression model in[ 10 ]. in particular the new method identifies two additional sites in the 61-90 region as sites that change h ...
values are parameters to be optimized. Hence, a modification of Bayesian networks in order to handle continuous variables is an important problem in the gene network estimation problem. A possible solution of this problem is given by using the nonparametric regression introduced in the next section....