Related Experiment Video
Updated: Oct 8, 2026

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
Published on: October 11, 2018
Empirical Bayes estimation for combinations of multivariate bioassays
D G Chen1, E M Carter, J J Hubert
1Department of Fisheries and Oceans, Government of Canada, Nanaimo, British Columbia. chend@dfo-mpo.gc.ca
Abstract:
This article presents a new empirical Bayes estimator (EBE) and a shrinkage estimator for determining the relative potency from several multivariate bioassays by incorporating prior information on the model parameters based on Jeffreys' rules. The EBE can account for any extra variability among the bioassays, and if this extra variability is 0, then the EBE reduces to the maximum likelihood estimator for combinations of multivariate bioassays. The shrinkage estimator turns out to be a compromise of the prior information and the estimator from each multivariate bioassay, with the weights depending on the prior variance.
Related Concept Videos
Probability Laws
Mechanistic Models: Compartment Models in Individual and Population Analysis
Biostatistics: Overview
Discrete variables are...
One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation
On...
Testing a Claim about Population Proportion
There are two methods of testing a claim about a population proportion: (1) Using the sample proportion from the data where a binomial distribution is approximated to the normal distribution and (2) Using the binomial probabilities calculated from the data.
The first method uses normal distribution as an approximation to the binomial distribution. The requirements are as follows: sample size is large...
Determination of Expected Frequency

