Analysis of Longitudinal Data
Author Description
The First Edition Of Analysis For Longitudinal Data Has Become A Classic. Describing The Statistical Models And Methods For The Analysis Of Longitudinal Data, It Covers Both The Underlying Statistical Theory Of Each Method, And Its Application To A Range Of Examples From The Agricultural And Biomedical Sciences. The Main Topics Discussed Are Design Issues, Exploratory Methods Of Analysis, Linear Models For Continuous Data, General Linear Models For Discrete Data, And Models And Methods For Handling Data And Missing Values. Under Each Heading, Worked Examples Are Presented In Parallel With The Methodological Development, And Sufficient Detail Is Given To Enable The Reader To Reproduce The Author's Results Using The Data-sets As An Appendix. This Second Edition, Published For The First Time In Paperback, Provides A Thorough And Expanded Revision Of This Important Text. It Includes Two New Chapters; The First Discusses Fully Parametric Models For Discrete Repeated Measures Data, And The Second Explores Statistical Models For Time-dependent Predictors.
Menrva's Summary
THE THESIS
This text investigates the statistical models and methodologies required to analyze longitudinal data, where observations are collected repeatedly over time from the same subjects. The authors, all distinguished experts in biostatistics and epidemiology, synthesize theoretical frameworks with practical applications to address the complexities of correlated data. By bridging the gap between mathematical theory and empirical implementation, the book provides a rigorous structure for researchers to interpret longitudinal trends in biomedical and agricultural fields.
THE SCOPE MAP
What You Will Find
- Linear models for continuous longitudinal data
- Generalized linear models for discrete repeated measures
- Methods for handling missing data and time-dependent predictors
- Exploratory data analysis techniques and study design considerations
- Worked examples with reproducible datasets
Scope Limits
- The text assumes a strong foundation in statistical theory and calculus
- It does not cover non-parametric longitudinal methods in depth
THE AUTHORITY PERSPECTIVE
Experts and academics widely regard this work as a foundational text for graduate-level biostatistics and longitudinal analysis. Readers frequently note the high level of technical density, which requires significant mathematical proficiency to fully utilize the provided models.
Page Count:
400
Publication Date:
2002-01-01
Publisher:
Oxford University Press
ISBN-10:
0191664324
ISBN-13:
9780191664328
Science
Biostatistics
Reference
Data Analysis
Mathematics
Statistics
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