Biostatistics M.A. Thesis
"Generalized application of empirical Bayes statistics to asymptotically linear parameters," a thesis submitted in partial satisfaction of the requirements for the Master of Arts in Biostatistics, at UC Berkeley, by Nima Hejazi.
This thesis presents a generalized approach for employing empirical Bayes moderation to improve the stability of estimates of variable importance measures (VIMs) using Targeted Minimum Loss-Based Estimation (TMLE), primarily in the context of problems often encountered in high-dimensional biology.
The compiled thesis document (in PDF) is available for browsing here.
This master's thesis has officially been accepted by the Graduate Division of UC Berkeley, with an effective filing date of 22 March 2017.
biotmle- R package that facilitates biomarker discovery by generalizing the moderated t-statistic of Smyth for use with asymptotically linear target parameters using Targeted Minimum Loss-Based Estimation.
make all- compile the thesis document, generating two subdirectories:
output(containing auxiliary documents created in the compilation process).
make clean- removes the subdirectories generated by the use of
n.b., a functional installation of a LaTeX distribution (e.g., MacTeX) is required to compile this thesis document.
© 2017 Nima S. Hejazi
The contents of this repository are released under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (CC BY-NC-SA 4.0)