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
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 ...
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 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 ...
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....
Linear regression, as a versatile tool, empowers professionals in marketing, finance, healthcare, retail, to name a few, to make data-driven decisions, optimize strategies, and improve overall performance. The significance of causal estimation lies in its ability to guide interventions, enhance ...
A Bayesian network meta-analysis was performed to assess postoperative pain management, with subgroup analyses and meta-regression conducted to examine key factors influencing outcomes, such as the risk of bias, continuous catheter analgesia, and patient-controlled analgesia (PCA). Results The results ...
In addition to prediction accuracy, we assessed the calibration of polygenic prediction methods by regressing the true phenotype onto the PRS predictor and inspecting the regression slope. A slope close to one indicates that a predictor is correctly calibrated. Consistent with predictive performance, as...
Using several breast cancer-specific datasets, we demonstrated the effectiveness of Bayesian network modeling in biological meaningful signal discovery, in comparison with methods of linear regression. Potentially, Bayesian inference can be used to infer dynamic GRN during cell differentiation using new ...
This will be done using the following bilogistic regression model for the meta-analysis of one test: ∑ i=k B = β [1] + β [2]S + ηi Xi , (12) i =1 1.0 0.9 0.8 0.7 TPR2 0.6 FPR2 TPR1 0.5 FPR1 0.0 0.1 0.2 0.3 0.4 Figure 3 Summary receiver operating characteristic ...