Statistical Inference Methods for Behavioral Genetics and Neuroeconomics
Forschungsprojekt “Statistical Inference Methods for Behavioral Genetics and Neuroeconomics”
Multiple tests are needed in behavioral genetics in order to analyze associations between many genetic markers and behavioral phenotypes simultaneously. In neuroeconomics, high-dimensional functional magnetic resonance imaging (fMRI) time series have to be analyzed with multiple testing techniques. This project contributes to behavioral genetics and neuroeconomics by developing refined statistical inference methods for data generated in these fields. In particular, techniques for multiple hypotheses testing will be refined, adapted, newly worked out, and applied to existing data sets in behavioral genetics.
The methods we develop are not restricted to such types of data, but will be applicable in many other fields, too: High-dimensional categorical data are also prevalent, for example, in genetic epidemiology or biometrics (multiple endpoint analyses), and high-dimensional hierarchical data structures occur for instance in spatial statistics or in the context of the analysis of variance, if the number of groups is large.
This project is jointly conducted with Prof. Dr. Thorsten Dickhaus (Universität Bremen) and is funded by the Germany National Science Foundation (DFG) (http://www.dfg.de/en/).