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

By:

Irimata, Katherine E, 1990- [Author]

Contributor(s):

Material type: Text

text

Media type:

computer

Carrier type:

online resource

ISBN:

9781421436722

Subject(s):

Genre/Form:

Electronic Books.

LOC classification:

RC523 .F863 2020

Online resources:

Click to access digital title | log in using your CIU ID number and my.ciu.edu password

Available additional physical forms:

Contents:

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.

Subject: "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"--

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Holdings
Item type	Current library	Collection	Call number	URL	Status	Date due	Barcode
Online Book (LOGIN USING YOUR MY CIU LOGIN AND PASSWORD)	G. Allen Fleece Library ONLINE	Non-fiction	RC523 (Browse shelf(Opens below))	Link to resource	Available		on1144942531

Includes bibliographies and index.

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.

"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"--

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