Alzheimer's disease is a devastating condition that presents overwhelming challenges to patients and caregivers. In the face of this relentless and as-yet incurable disease, mastery of statistical analysis is paramount for anyone who must assess complex data that could improve treatment options. This unique book presents up-to-date statistical techniques commonly used in the analysis of data on Alzheimer's and other neurodegenerative diseases.
With examples drawn from the real world that will make it accessible to disease researchers, practitioners, academics, and students alike, this volume
presents code for analyzing dementia data in statistical programs, including SAS, R, SPSS, and Stata
introduces statistical models for a range of data types, including continuous, categorical, and binary responses, as well as correlated data
draws on datasets from the National Alzheimer's Coordinating Center, a large relational database of standardized clinical and neuropathological research data
discusses advanced statistical methods, including hierarchical models, survival analysis, and multiple-membership
examines big data analytics and machine learning methods
Easy to understand but sophisticated in its approach, Fundamental Statistical Methods for Analysis of Alzheimer's and Other Neurodegenerative Diseases will be a cornerstone for anyone looking for simplicity in understanding basic and advanced statistical data analysis topics. Allowing more people to aid in analyzing data'while promoting constructive dialogues with statisticians'this book will hopefully play an important part in unlocking the secrets of these confounding diseases.
1. Introduction to Statistical Software and Alzheimer's Data2. Review of Introductory Statistical Methods3. Generalized Linear Models4. Hierarchical Regression Models for Continuous Responses5. Hierarchical Logistic Regression Models6. Bayesian Regression Models7. Multiple Membership Models8. Survival Data Analysis9. Modeling Responses with Time-dependent Covariates10. Joint Modeling of Mean and Dispersion11. Neural Networks and Other Machine Learning Techniques for Big Data12. Case StudyReferencesAcknowledgments
Researchers focused on the field of Alzheimer's disease and other neurodegenerative diseases, who are not statisticians themselves but are interested in expanding their knowledge and/or capability, will wantto read this book.Thomas G.Beach, MD, PhD, Banner Sun Health Research Institute
