Reviews
Making recent and existing statistical methods for analyzing data of Alzheimer's disease and other dementias accessible, this book is also useful to researchers and practitioners in other related health areas. The authors enable practitioners, including people who may not have a strong mathematical background, to understand statistical tools and effectively use statistical software. A useful reference that will greatly benefit readers.
This nicely written, example-oriented volume offers wide utility to statistics professors. It will be particularly appealing in introductory undergraduate statistics courses.
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 want to read this book. A very original and substantial contribution to the field.
Book Details
1. Introduction to Statistical Software and Alzheimer's Data
2. Review of Introductory Statistical Methods
3. Generalized Linear Models
4. Hierarchical Regression Models for Continuous Responses
5
1. Introduction to Statistical Software and Alzheimer's Data
2. Review of Introductory Statistical Methods
3. Generalized Linear Models
4. Hierarchical Regression Models for Continuous Responses
5. Hierarchical Logistic Regression Models
6. Bayesian Regression Models
7. Multiple Membership Models
8. Survival Data Analysis
9. Modeling Responses with Time-dependent Covariates
10. Joint Modeling of Mean and Dispersion
11. Neural Networks and Other Machine Learning Techniques for Big Data
12. Case Study
References
Acknowledgments