Fundamental statistical methods for analysis of Alzheimer's and other neurodegenerative diseases / Katherine E. Irimata, Brittany N. Dugger, Jeffrey R. Wilson ; foreword by Marwan Sabbagh.

Format:

Book

Author/Creator:

Irimata, Katherine E., 1990- author.

Dugger, Brittany N., author.

Wilson, Jeffrey R., author.

Contributor:

Sabbagh, Marwan, writer of foreword.

Language:

English

Subjects (All):

Statistics as Topic.

Biometry.

Alzheimer's disease.

Physical Description:

1 online resource

Place of Publication:

Baltimore : Johns Hopkins University Press, 2020.

Summary:

"This book explains statistical techniques commonly used in analyzing data for Alzheimer's and other neurodegenerative diseases, and it presents examples from real-world applications in an effort to make the techniques useful for professionals and students. The book leads readers through the steps of conducting multivariate analyses while adjusting for correlation or the hierarchical structure of data in prediction and inferences. Techniques such as spatial analysis, Bayesian analysis, and time-dependent covariates are included. Several data sets from the National Alzheimer's Coordinating Center are analyzed with statistical software commonly used by Alzheimer's researchers, and the results are shown to readers by way of illustration"-- Provided by publisher.

Contents:

Introduction to Statistical Software and Alzheimer's Data

Review of Introductory Statistical Methods

Generalized Linear Models

Hierarchical Regression Models for Continuous Responses

Hierarchical Logistic Regression Models

Bayesian Regression Models

Multiple Membership Models

Survival Data Analysis

Modeling Responses with Time-Dependent Covariates

Joint Modeling of Mean and Dispersion

Neural Networks and Other Machine Learning Techniques for Big Data

Case Study.

Notes:

Includes bibliographical references and index.

Description based on print version record.

ISBN:

1-4214-3672-8

OCLC:

1144942531