Adaptive Experiments and a Rigorous Framework for Type I Error Verification and Computational Experiment Design
Methodology
2022-05-20 v1
Abstract
This PhD thesis covers breakthroughs in several areas of adaptive experiment design: (i) (Chapter 2) Novel clinical trial designs and statistical methods in the era of precision medicine. (ii) (Chapter 3) Multi-armed bandit theory, with applications to learning healthcare systems and clinical trials. (iii) (Chapter 4) Bandit and covariate processes, with finite and non-denumerable set of arms. (iv) (Chapter 5) A rigorous framework for simulation-based verification of adaptive design properties.
Cite
@article{arxiv.2205.09369,
title = {Adaptive Experiments and a Rigorous Framework for Type I Error Verification and Computational Experiment Design},
author = {Michael Sklar},
journal= {arXiv preprint arXiv:2205.09369},
year = {2022}
}
Comments
See chapter 5 for proof-by-simulation material not published elsewhere. Minor corrections have been made to the 2021 original document. See https://mikesklar.github.io/thesis/ for the most current maintained version