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JSS Research Series in Statistics

Longitudinal Data Analysis

Autoregressive Linear Mixed Effects Models

Authors: Funatogawa, Ikuko, Funatogawa, Takashi

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  • Describes a new analytical approach for longitudinal data, autoregressive linear mixed effects models, in which dynamic models are induced by the auto-regression term
  • Provides state space representation of autoregressive linear mixed models with the modified Kalman filter for the calculation of log likelihoods
  • Is written in plain English dealing not only with topics for those in medical fields but that is also understandable for researchers in other disciplines
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eBook 44,02 €
price for Spain (gross)
  • ISBN 978-981-10-0077-5
  • Digitally watermarked, DRM-free
  • Included format: PDF, EPUB
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Softcover 57,19 €
price for Spain (gross)
  • ISBN 978-981-10-0076-8
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
  • The final prices may differ from the prices shown due to specifics of VAT rules
About this book

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.

About the authors

Ikuko Funatogawa, The Institute of Statistical Mathematics
Takashi Funatogawa, Chugai Pharmaceutical Co. Ltd.

Table of contents (6 chapters)

Table of contents (6 chapters)

Buy this book

eBook 44,02 €
price for Spain (gross)
  • ISBN 978-981-10-0077-5
  • Digitally watermarked, DRM-free
  • Included format: PDF, EPUB
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Softcover 57,19 €
price for Spain (gross)
  • ISBN 978-981-10-0076-8
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
  • The final prices may differ from the prices shown due to specifics of VAT rules
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Bibliographic Information

Bibliographic Information
Book Title
Longitudinal Data Analysis
Book Subtitle
Autoregressive Linear Mixed Effects Models
Authors
Series Title
JSS Research Series in Statistics
Copyright
2018
Publisher
Springer Singapore
Copyright Holder
The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd.
eBook ISBN
978-981-10-0077-5
DOI
10.1007/978-981-10-0077-5
Softcover ISBN
978-981-10-0076-8
Series ISSN
2364-0057
Edition Number
1
Number of Pages
X, 141
Number of Illustrations
27 b/w illustrations
Topics