Methods and Applications of Longitudinal Data Analysis describes methods for the analysis of longitudinal data in the medical, biological and behavioral sciences, introducing basic concepts and functions, 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, and techniques for analyzing longitudinal data with non-ignorable missing observations. Given the targeted audience of the book, the authors emphasize applications of these methods, using substantial empirical illustrations, designed to help users of statistics better analyze and understand longitudinal data. The text is suitable for both graduate students and professions who are interested in longitudinal data analysis. Applied statisticians and other quantitative methodologists can also use the book as a convenient reference. From novice to professional: This book starts with the introduction of basic models and ends with the description of some most advanced topics in longitudinal data analysisWith plenty of empirical examples, students can read and study smoothly.The book introduces both classical repeated measures models and newly developed techniques with real-world examples. INDICE: 1 Introduction 2 Traditional Methods of Longitudinal Data Analysis 3 Linear Mixed-effects Models on Continuous Responses 4 Marginal Linear Models with Random Effects 5 Inference and Estimation of Random Effects for Linear Mixed-effects Models 6 Patterns of Residual Covariance Structure 7 Comparison of Random-effects and Covariance Pattern Perspectives 8 Diagnostics of Mixed-effects Linear Regression Models 9 Nonlinear Regression Modeling on Longitudinal Data 10 Generalized Estimating Equations Models (GEE) 11 Mixed-effects Regression Models for Binary Outcome Data 12 Random-effects Regression Models for Ordered Categorical Outcomes 13 Random-effects Multinomial Logit Regression for Nominal Outcome Data 14 Longitudinal Transition Models for Categorical Outcome Data 15 Methods for Handling Missing Data Bibliography Index
- ISBN: 978-0-12-801342-7
- Editorial: Academic Press
- Encuadernacion: Cartoné
- Páginas: 400
- Fecha Publicación: 12/02/2016
- Nº Volúmenes: 1
- Idioma: Inglés