statistical inference via empirical bayes approach for stationary and dynamic contingency tables
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An empirical Bayes approach to inferring large-scale gene association networks
MOTIVATION Genetic networks are often described statistically using graphical models (e.g. Bayesian networks). However, inferring the network structure offers a serious challenge in microarray analysis where the sample size is small compared to the number of considered genes. Thi
Optimal post-selection inference for sparse signals: a nonparametric empirical Bayes approach
Summary Many recently developed Bayesian methods focus on sparse signal detection. However, much less work has been done the natural follow-up question: how does one make valid inferences for magnitude of those signals after selection? Ordinary credible intervals suffer from sele
An Empirical Bayes Approach to Combining and Comparing Estimates of the Value of a Statistical Life for Environmental Policy Analysis
An empirical Bayes pooling method is used to combine and compare estimates of the value of a statistical life (VSL). The data come from 40 selected studies published between 1974 and 2002, containing 197 VSL estimates. The estimated composite distribution of empirical Bayes adjus
An Empirical Bayes Approach to Robust Variance Estimation: A Statistical Proposal for Quantitative Medical Image Testing
The current standard for measuring tumor response using X-ray, CT and MRI is based on the response evaluation criterion in solid tumors (RECIST) which, while providing simplifications over previous (WHO) 2-D methods, stipulate four response categories: CR (complete response), PR
An empirical Bayes approach to identification of modules in dynamic networks
We present a new method of identifying a specific module in a dynamic network, possibly with feedback loops. Assuming known topology, we express the dynamics by an acyclic network composed of two blocks where the first block accounts for the relation between the known reference s
Improving polygenic risk prediction from summary statistics by an empirical Bayes approach
Polygenic risk scores (PRS) from genome-wide association studies (GWAS) are increasingly used to predict disease risks. However some included variants could be false positives and the raw estimates of effect sizes from them may be subject to selection bias. In addition, the stand