Observational data, although readily available, is sensitive to biases such as confounding by indication. Structure learning algorithms for Bayesian Networks (BNs) can be used to discover the ...

Jenny Häggström, Data-Driven Confounder Selection via Markov and Bayesian Networks, Biometrics, Vol. 74, No. 2 (JUNE 2018), pp. 389-398 ...

The node-splitting method was used to examine local inconsistency between direct, indirect and network estimates, and statistical inconsistency was considered when p≤0.05. 36 If significant ...

WHAT THIS STUDY ADDS This network meta-analysis is the largest synthesis of resistance training prescription data from randomised trials. All resistance training prescriptions are better than no ...

GRENOBLE, France – Dec. 7, 2023 – A team comprising CEA-Leti, CEA-List and two CNRS laboratories has published a paper in Nature Communications presenting what the authors said is the first complete ...

An international research team led by scientists from Osaka Metropolitan University has developed a method to identify symmetries in multi-dimensional data using Bayesian statistical techniques ...