We find that our preferred Bayesian Nonlinear Meta-Regression Model (BNL-MRM) satisfies all theoretical requirements. Using a built-in nonlinear model search algorithm we show that it produces benefit estimates
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 ...
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...
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 ...
which measures the mutual dependence between the two nodes in the Bayesian Network. In[93], another Bayesian Network-based model was proposed, where authors used the Multiregression Dynamic Model (MDM) to improve forecasts.MDMis designed to preserve certain conditional independent structures over time...
The true and false positive rates are transformed so that one may use bilogistic regression to determine the accuracy of the combined tests where the posterior distribution of the parameters of the model are determined. Bayesian inferences are based on the posterior distribution of the SROC curve ...
In line 13, we reshape the data to the required 2D format for scikit-learn’s LinearRegression model. The model estimates the effect of compulsory schooling on education, isolating the variation in education directly caused by the instrument (compulsory schooling) and removing the influence of abil...
regression model with a generalization of the dirichlet process prior on the distribution of the regression coefficients that describes the relationship between the changes in amino acid distances and natural selection in protein-coding dna sequence alignments. results the bayesian semiparametric approach is...
network meta‐analysisrandom‐effects modelsimulation studyThe performance of statistical methods is often evaluated by means of simulation studies. In case of network meta゛nalysis of binary data, however, simulations are not currently available for many practically relevant settings.We perform a ...