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Methods and Applications of Longitudinal Data Analysis

by Xian Liu

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A methods-focused guide to analyzing change over time

$174.42 USD
$174.42 USD $174.42 USD

Hardcover New English

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AlbakiReads Editorial

A methods-focused guide to analyzing change over time

Centered on longitudinal data from medical, biological, and behavioral research, this volume brings together statistical approaches for studying repeated observations and trends across time. It moves from descriptive tools into a broad range of regression-based methods, including linear mixed models, covariance-pattern models, generalized estimating equations, nonlinear models for categorical repeated measurements, and approaches for non-ignorable missing data. Empirical illustrations keep the emphasis on application, showing how these procedures can be used across research settings. The book also distinguishes fixed and random effects and addresses correlated errors, making it a substantial reference for the practical complications that arise when observations are not independent.

Good fit for readers who enjoy

  • Graduate students studying applied longitudinal methods
  • Researchers in medical, biological, or behavioral sciences
  • Applied statisticians, demographers, and quantitative methodologists

Themes

Longitudinal data analysisRepeated measurementsRegression modelingMissing dataApplied statistical methods

Based on publisher information and book metadata.

Book overview

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.

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