marcoapintoo / statistics-epilepsy-book

Statistical Methods in Epilepsy

Statistical Methods in Epilepsy, 1st Edition

Editors: Sharon Chiang, Vikram R. Rao, and Marina Vannucci

Statistical Methods in Epilepsy is an introductory textbook for statistics published by Chapman & Hall in 2024. It covers foundational skills in programming and statistics with a focus on example applications from epilepsy research.

This repository holds the R and Jupyter notebook source code for individual book chapters.

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We encourage readers to send us comments or typos they detect in any of the chapters.

To propose changes to the code for any chapter:

1. Get your copy of this repository:

   git clone https://github.com/sharon-chiang/Statistics-Epilepsy-Book.git
   

2. Change the file you wish and commit it to the repository.

3. Push your change back to the repository via a pull request.

Table of Contents with Supporting Material:

Chapter 1. Coding Basics
Emilian R. Vankov, Rob M. Sylvester and Christfried H. Focke

Chapter 2. Preprocessing Electrophysiological Data: EEG, iEEG and MEG Data
Kristin K. Sellers, Joline M. Fan, Leighton B.N. Hinkley and Heidi E. Kirsch

Chapter 3. Acquisition and Preprocessing of Neuroimaging MRI Data
Hsiang J. Yeh

Chapter 4. Hypothesis Testing and Correction for Multiple Testing
Doug Speed

Chapter 5. Introduction to Linear, Generalized Linear and Mixed-Effects Models
Omar Vazquez, Xiangmin Xu and Zhaoxia Yu

Chapter 6. Survival Analysis
Fei Jiang and Elan Guterman

Chapter 7. Graph and Network Control Theoretic Frameworks
Ankit N. Khambhati and Sharon Chiang

Chapter 8. Time-Series Analysis
Sharon Chiang, John Zito, Vikram R. Rao, and Marina Vannucci

Chapter 9. Spectral Analysis of Electrophysiological Data
Hernando Ombao and Marco Antonio Pinto-Orellana

Chapter 10. Spatial Modeling of Imaging and Electrophysiological Data
Rongke Lyu, Michele Guindani and Marina Vannucci

Chapter 11. Unsupervised Learning
Giuseppe Vinci

Chapter 12. Supervised Learning
Emilian R. Vankov and Kais Gadhoumi

Chapter 13. Natural Language Processing
Christfried H. Focke and Rob M. Sylvester

Chapter 14. Prospective Observational Study Design and Analysis
Carrie Brown, Kimford J. Meador, Page Pennell, and Abigail G. Matthews

Chapter 15. Pharmacokinetic and Pharmacodynamic Modeling
Ashwin Karanam, Yuhan Long and Angela Birnbaum

Chapter 16. Randomized Clinical Trial Analysis
Joseph E. Sullivan and Michael Lock