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Longitudinal Data Analysis: Autoregressive Linear Mixed Effects Models (JSS Research Series in Statistics) - Softcover
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...
About the Author
Ikuko Funatogawa, The Institute of Statistical Mathematics
Takashi Funatogawa, Chugai Pharmaceutical Co. Ltd.
"About this title" may belong to another edition of this title.
- PublisherSpringer
- Publication date2019
- ISBN 10 981100076X
- ISBN 13 9789811000768
- BindingPaperback
- LanguageEnglish
- Edition number1
- Number of pages151
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Longitudinal Data Analysis: Autoregressive Linear Mixed Effects Models
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Longitudinal Data Analysis : Autoregressive Linear Mixed Effects Models
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Longitudinal Data Analysis : Autoregressive Linear Mixed Effects Models
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Longitudinal Data Analysis
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Springer Nature Singapore Feb 2019, 2019
ISBN 10: 981100076X
ISBN 13: 9789811000768
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Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 152 pp. Englisch. Seller Inventory # 9789811000768
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Longitudinal Data Analysis : Autoregressive Linear Mixed Effects Models
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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Condition: New. Seller Inventory # 26739483-n
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Longitudinal Data Analysis : Autoregressive Linear Mixed Effects Models
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Springer Nature Singapore, Springer Nature Singapore, 2019
ISBN 10: 981100076X
ISBN 13: 9789811000768
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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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. Seller Inventory # 9789811000768
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Longitudinal Data Analysis
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Describes a new analytical approach for longitudinal data, autoregressive linear mixed effects models, in which dynamic models are induced by the auto-regression termProvides state space representation of autoregressive linear. Seller Inventory # 82810914
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Longitudinal Data Analysis: Autoregressive Linear Mixed Effects Models
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Paperback. Condition: Brand New. 152 pages. 9.25x6.25x0.50 inches. In Stock. Seller Inventory # zk981100076X
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