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Item Details
Title: LONGITUDINAL DATA ANALYSIS
AUTOREGRESSIVE LINEAR MIXED EFFECTS MODELS
Volume: 2016
By: Ikuko Funatogawa, Takashi Funatogawa
Format: Paperback

List price: £54.99
Our price: £48.12
Discount:
12.5% off
You save: £6.87
ISBN 10: 981100076X
ISBN 13: 9789811000768
Availability: Usually dispatched within 1-3 weeks.
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Stock: Currently 0 available
Publisher: SPRINGER VERLAG, SINGAPORE
Pub. date: 28 January, 2017
Series: SpringerBriefs in Statistics
Pages: 100
Synopsis: 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.
Illustrations: biography
Publication: Singapore
Imprint: Springer Verlag, Singapore
Returns: Returnable

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