Longitudinal Data Analysis

Name: Longitudinal Data Analysis
Brand: Springer Verlag, Singapore
SKU: 9789811000768
Price: 332.57 RON
Availability: InStock

Autoregressive Linear Mixed Effects Models

Autor: Ikuko Funatogawa, Takashi Funatogawa

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Legare: Carte broșată

Editura: Springer Verlag, Singapore

Disponibilitate: În depozitul extern

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332.57 lei

This book provides a new analytical approach for dynamic data repeatedly measured from multiple subj...

Informații despre carte

Autor

Ikuko Funatogawa, Takashi Funatogawa

Limbă

engleză

Legare

Carte - Carte broșată

Publicat

2018

Pagini

141

EAN

9789811000768

ISBN

981100076X

Enbook ID

02823380

Editura

Springer Verlag, Singapore

Greutate

243

Dimensiuni

155 x 235 x 9

Descriere completă

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.

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Longitudinal Data Analysis

Autoregressive Linear Mixed Effects Models

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