Methods and Applications of Longitudinal Data Analysis

Liu, Xian:

ISBN 10: 0128013427 ISBN 13: 9780128013427

Published by Academic Press, 2015

Language: English

Condition: Used - Fine Hardcover

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530 Seiten; 9780128013427.2 Gewicht in Gramm: 2.

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Bibliographic Details

Title

Methods and Applications of Longitudinal Data Analysis

Publisher

Academic Press

Publication Date

2015

Language

English

ISBN 10

0128013427

ISBN 13

9780128013427

Binding

hardcover

Condition

Sehr gut

Weight

2 grams

Seller catalogs

Varia

About this title

Synopsis

Methods and Applications of Longitudinal Data Analysis describes methods for the analysis of longitudinal data in the medical, biological and behavioral sciences. It introduces basic concepts and functions including a variety of regression models, and their practical applications across many areas of research. Statistical procedures featured within the text include:

descriptive methods for delineating trends over time
linear mixed regression models with both fixed and random effects
covariance pattern models on correlated errors
generalized estimating equations
nonlinear regression models for categorical repeated measurements
techniques for analyzing longitudinal data with non-ignorable missing observations

Emphasis is given to applications of these methods, using substantial empirical illustrations, designed to help users of statistics better analyze and understand longitudinal data.

Methods and Applications of Longitudinal Data Analysis equips both graduate students and professionals to confidently apply longitudinal data analysis to their particular discipline. It also provides a valuable reference source for applied statisticians, demographers and other quantitative methodologists.

From novice to professional: this book starts with the introduction of basic models and ends with the description of some of the most advanced models in longitudinal data analysis
Enables students to select the correct statistical methods to apply to their longitudinal data and avoid the pitfalls associated with incorrect selection
Identifies the limitations of classical repeated measures models and describes newly developed techniques, along with real-world examples.

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