A Bayesian meta-regression model was employed, using the risk difference metric to estimate the relationship between mortality difference and control arm risk, and estimate the mortality difference with and wit
Motivated by these limitations, our research proposes a nonparametric Bayesian meta-regression which relaxes parametric assumptions and incorporates functional meta-predictors and spatial dependency. The proposed meta-regression is formulated by jointly modeling the association parameters and the functional meta...
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 ...
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 ...
meta-analysisSROC curveLyle D BroemelingBroemeling amp;amp; Associates Inc, Medical Lake, WA, USAAbstract: Determining the accuracy of a medical test is quite difficult because accuracy is an elusive parameter to estimate. A common scenario is estimating the true and false positive fractions from...
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 ...
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....
VariableSubgroupStudies (n)ORa (95% CI)P value, I2Meta-regressionGradePublication bias, P value MMSEb (score) Overall (all activity control) N/Ac 3 1.557 (–0.459 to 3.572) <.001, 95.5%d —e Low 0.296, .37 Intervention type Xbox 360 1 4.606 (3.366-5.846) — 0.095f — — Interve...