Fundamental Statistical Methods for Analysis of Alzheimer's and Other Neurodegenerative Diseases Lead Investigator: Katherine Irimata Institution : Arizona State University E-Mail : katherine.irimata@gmail.com Proposal ID : 987 Proposal Description: My co-authors and I are writing a textbook that presents statistical analyses and models for the use of Alzheimer's data, as well as other neurodegenerative diseases. This book will be extremely useful to Alzheimer's researchers and other practitioners, and is designed to serve as a cornerstone for anyone looking for simplicity in understanding advanced topics in statistical data analysis. The book is full of examples (using a variety of software, including SAS, STATA, SPSS, and R) and can be used as a reference for researchers or as a course book. We aim to address a critical barrier to progress in the field by providing an easily understandable resource in statistics that appeals to researchers working with Alzheimer's data. Many topics will be covered in the book, including basic statistical testing and models, generalized linear models, mixed models and generalized estimating equations for evaluating hierarchical and longitudinal data, multiple membership models, survival analysis, as well as correlated and time-dependent data analyses. The book will focus on examples of interest in neurodegenerative disease research, including predicting dementia diagnosis, evaluating changes in cognition, and identifying common risk factors. We will feature comparisons between non-demented, AD, DLB, FTD, and VaD patients, as well as mixed pathologies. The textbook will conclude with a case study to evaluate a data set from start to finish, including reviewing the data, performing statistical analyses, and interpreting the results.