Name: Longitudinal Data Analysis: Autoregressive Linear Mixed Effects Models (Springerbriefs in Statistics) (en Inglés)
SKU: 51501660
Price: 201.00 PEN
Availability: InStock
Author: Ikuko Funatogawa
ISBN: 9789811000768

portada Longitudinal Data Analysis: Autoregressive Linear Mixed Effects Models (Springerbriefs in Statistics) (en Inglés)

Longitudinal Data Analysis: Autoregressive Linear Mixed Effects Models (Springerbriefs in Statistics) (en Inglés)

Formato

Libro Físico

Editorial

Springer

Autor

Ikuko Funatogawa

Año

2019

Idioma

Inglés

N° páginas

152

Encuadernación

Tapa Blanda

ISBN13

9789811000768

N° edición

Categorías

Software de matemáticas y estadísticas

Longitudinal Data Analysis: Autoregressive Linear Mixed Effects Models (Springerbriefs in Statistics) (en Inglés)

Ikuko Funatogawa (Autor) · Springer · Tapa Blanda

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Reseña del libro "Longitudinal Data Analysis: Autoregressive Linear Mixed Effects Models (Springerbriefs in Statistics) (en Inglés)"

This book provides a new analytical approach for dynamic data repeatedly measured from multiple subjects over time. Random effects account for differences across subjects. Auto-regression in response itself is often used in time series analysis. In longitudinal data analysis, a static mixed effects model is changed into a dynamic one by the introduction of the auto-regression term. Response levels in this model gradually move toward an asymptote or equilibrium which depends on covariates and random effects. The book provides relationships of the autoregressive linear mixed effects models with linear mixed effects models, marginal models, transition models, nonlinear mixed effects models, growth curves, differential equations, and state space representation. State space representation with a modified Kalman filter provides log likelihoods for maximum likelihood estimation, and this representation is suitable for unequally spaced longitudinal data. The extension to multivariate longitudinal data analysis is also provided. Topics in medical fields, such as response-dependent dose modifications, response-dependent dropouts, and randomized controlled trials are discussed. The text is written in plain terms understandable for researchers in other disciplines such as econometrics, sociology, and ecology for the progress of interdisciplinary research.