Longitudinal Data With Serial Correlation
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Longitudinal Data With Serial Correlation
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Author : Richard .H. Jones
language : en
Publisher: CRC Press
Release Date : 2018-05-04
Longitudinal Data With Serial Correlation written by Richard .H. Jones and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-05-04 with Mathematics categories.
This monograph is written for students at the graduate level in biostatistics, statistics or other disciplines that collect longitudinal data. It concentrates on the state space approach that provides a convenient way to compute likelihoods using the Kalman filter.
Longitudinal Data With Serial Correlation
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Author : Richard Hunn Jones
language : en
Publisher:
Release Date : 1993
Longitudinal Data With Serial Correlation written by Richard Hunn Jones and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1993 with Longitudinal method categories.
Unbalanced Designs And Serial Correlation In Longitudinal Data
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Author : Francis Boadi-Boateng
language : en
Publisher:
Release Date : 1986
Unbalanced Designs And Serial Correlation In Longitudinal Data written by Francis Boadi-Boateng and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1986 with categories.
Longitudinal Data With Serial Correlation
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Author : Richard .H. Jones
language : en
Publisher: CRC Press
Release Date : 2018-05-04
Longitudinal Data With Serial Correlation written by Richard .H. Jones and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-05-04 with Mathematics categories.
This monograph is written for students at the graduate level in biostatistics, statistics or other disciplines that collect longitudinal data. It concentrates on the state space approach that provides a convenient way to compute likelihoods using the Kalman filter.
Antedependence Models For Longitudinal Data
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Author : Dale L. Zimmerman
language : en
Publisher: CRC Press
Release Date : 2009-08-19
Antedependence Models For Longitudinal Data written by Dale L. Zimmerman and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-08-19 with Mathematics categories.
The First Book Dedicated to This Class of Longitudinal Models Although antedependence models are particularly useful for modeling longitudinal data that exhibit serial correlation, few books adequately cover these models. By gathering results scattered throughout the literature, Antedependence Models for Longitudinal Data offers a convenient, systematic way to learn about antedependence models. Illustrated with numerous examples, the book also covers some important statistical inference procedures associated with these models. After describing unstructured and structured antedependence models and their properties, the authors discuss informal model identification via simple summary statistics and graphical methods. They then present formal likelihood-based procedures for normal antedependence models, including maximum likelihood and residual maximum likelihood estimation of parameters as well as likelihood ratio tests and penalized likelihood model selection criteria for the model’s covariance structure and mean structure. The authors also compare the performance of antedependence models to other models commonly used for longitudinal data. With this book, readers no longer have to search across widely scattered journal articles on the subject. The book provides a thorough treatment of the properties and statistical inference procedures of various antedependence models.
A Simulation Study Of The Hierarchical Linear Model With Serially Correlated Longitudinal Data And Missing Values
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Author : Dean E. Nelson
language : en
Publisher:
Release Date : 1999
A Simulation Study Of The Hierarchical Linear Model With Serially Correlated Longitudinal Data And Missing Values written by Dean E. Nelson and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999 with Longitudinal method categories.
The hierarchical linear model (HLM) is becoming a common choice for analyzing longitudinal data. Theoretically, the HLM can explicitly model serial correlation, which is often found in longitudinal data, and can also provide unbiased parameter estimates in the presence of certain kinds of missing data. However, no empirical investigations comparing use of the HLM with more traditional models of analysis for longitudinal data have been performed. This study compares the HLM with repeated measures analysis of variance and multivariate analysis of variance in the presence of increasing levels of serial correlation. In addition, the study investigates the performance of the HLM under increasing levels of missingness, when the data are missing completely at random and when the data are missing at random.
Linear Mixed Models For Longitudinal Data
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Author : Geert Verbeke
language : en
Publisher: Springer Science & Business Media
Release Date : 2009-04-28
Linear Mixed Models For Longitudinal Data written by Geert Verbeke and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-04-28 with Mathematics categories.
This book provides a comprehensive treatment of linear mixed models for continuous longitudinal data. Next to model formulation, this edition puts major emphasis on exploratory data analysis for all aspects of the model, such as the marginal model, subject-specific profiles, and residual covariance structure. Further, model diagnostics and missing data receive extensive treatment. Sensitivity analysis for incomplete data is given a prominent place. Most analyses were done with the MIXED procedure of the SAS software package, but the data analyses are presented in a software-independent fashion.
Dynamic Mixed Models For Familial Longitudinal Data
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Author : Brajendra C. Sutradhar
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-01-27
Dynamic Mixed Models For Familial Longitudinal Data written by Brajendra C. Sutradhar and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-01-27 with Mathematics categories.
This book provides a theoretical foundation for the analysis of discrete data such as count and binary data in the longitudinal setup. Unlike the existing books, this book uses a class of auto-correlation structures to model the longitudinal correlations for the repeated discrete data that accommodates all possible Gaussian type auto-correlation models as special cases including the equi-correlation models. This new dynamic modelling approach is utilized to develop theoretically sound inference techniques such as the generalized quasi-likelihood (GQL) technique for consistent and efficient estimation of the underlying regression effects involved in the model, whereas the existing ‘working’ correlations based GEE (generalized estimating equations) approach has serious theoretical limitations both for consistent and efficient estimation, and the existing random effects based correlations approach is not suitable to model the longitudinal correlations. The book has exploited the random effects carefully only to model the correlations of the familial data. Subsequently, this book has modelled the correlations of the longitudinal data collected from the members of a large number of independent families by using the class of auto-correlation structures conditional on the random effects. The book also provides models and inferences for discrete longitudinal data in the adaptive clinical trial set up. The book is mathematically rigorous and provides details for the development of estimation approaches under selected familial and longitudinal models. Further, while the book provides special cares for mathematics behind the correlation models, it also presents the illustrations of the statistical analysis of various real life data. This book will be of interest to the researchers including graduate students in biostatistics and econometrics, among other applied statistics research areas. Brajendra Sutradhar is a University Research Professor at Memorial University in St. John’s, Canada. He is an elected member of the International Statistical Institute and a fellow of the American Statistical Association. He has published about 110 papers in statistics journals in the area of multivariate analysis, time series analysis including forecasting, sampling, survival analysis for correlated failure times, robust inferences in generalized linear mixed models with outliers, and generalized linear longitudinal mixed models with bio-statistical and econometric applications. He has served as an associate editor for six years for Canadian Journal of Statistics and for four years for the Journal of Environmental and Ecological Statistics. He has served for 3 years as a member of the advisory committee on statistical methods in Statistics Canada. Professor Sutradhar was awarded 2007 distinguished service award of Statistics Society of Canada for his many years of services to the society including his special services for society’s annual meetings.
Models For Discrete Longitudinal Data
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Author : Geert Molenberghs
language : en
Publisher: Springer Science & Business Media
Release Date : 2006-08-30
Models For Discrete Longitudinal Data written by Geert Molenberghs and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-08-30 with Mathematics categories.
The linear mixed model has become the main parametric tool for the analysis of continuous longitudinal data, as the authors discussed in their 2000 book. Without putting too much emphasis on software, the book shows how the different approaches can be implemented within the SAS software package. The authors received the American Statistical Association's Excellence in Continuing Education Award based on short courses on longitudinal and incomplete data at the Joint Statistical Meetings of 2002 and 2004.
Practical Longitudinal Data Analysis
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Author : David J. Hand
language : en
Publisher: CRC Press
Release Date : 1996-03-01
Practical Longitudinal Data Analysis written by David J. Hand and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1996-03-01 with Mathematics categories.
This text describes regression-based approaches to analyzing longitudinal and repeated measures data. It emphasizes statistical models, discusses the relationships between different approaches, and uses real data to illustrate practical applications. It uses commercially available software when it exists and illustrates the program code and output. The data appendix provides many real data sets-beyond those used for the examples-which can serve as the basis for exercises.