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.

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Summary

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.

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Notes

• 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.

Related

• 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.

Compilation

• make all - compile the thesis document, generating two subdirectories: pdf (containing the thesis and approval page in PDF) and output (containing auxiliary documents created in the compilation process).

• make clean - removes the subdirectories generated by the use of make all.

• n.b., a functional installation of a LaTeX distribution (e.g., MacTeX) is required to compile this thesis document.

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License

© 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)

A human-readable version of the CC BY-NC-SA 4.0 license is available here; the full license may be examined here.