Missing Data In Longitudinal Studies
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Missing Data In Longitudinal Studies
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Author : Michael J. Daniels
language : en
Publisher: CRC Press
Release Date : 2008-03-11
Missing Data In Longitudinal Studies written by Michael J. Daniels and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-03-11 with Mathematics categories.
Drawing from the authors’ own work and from the most recent developments in the field, Missing Data in Longitudinal Studies: Strategies for Bayesian Modeling and Sensitivity Analysis describes a comprehensive Bayesian approach for drawing inference from incomplete data in longitudinal studies. To illustrate these methods, the authors employ several data sets throughout that cover a range of study designs, variable types, and missing data issues. The book first reviews modern approaches to formulate and interpret regression models for longitudinal data. It then discusses key ideas in Bayesian inference, including specifying prior distributions, computing posterior distribution, and assessing model fit. The book carefully describes the assumptions needed to make inferences about a full-data distribution from incompletely observed data. For settings with ignorable dropout, it emphasizes the importance of covariance models for inference about the mean while for nonignorable dropout, the book studies a variety of models in detail. It concludes with three case studies that highlight important features of the Bayesian approach for handling nonignorable missingness. With suggestions for further reading at the end of most chapters as well as many applications to the health sciences, this resource offers a unified Bayesian approach to handle missing data in longitudinal studies.
Applied Longitudinal Data Analysis For Epidemiology
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Author : Jos W. R. Twisk
language : en
Publisher: Cambridge University Press
Release Date : 2013-05-09
Applied Longitudinal Data Analysis For Epidemiology written by Jos W. R. Twisk and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-05-09 with Medical categories.
A practical guide to the most important techniques available for longitudinal data analysis, essential for non-statisticians and researchers.
Applied Linear Regression For Longitudinal Data
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Author : Frans E.S. Tan
language : en
Publisher: CRC Press
Release Date : 2022-12-09
Applied Linear Regression For Longitudinal Data written by Frans E.S. Tan and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-12-09 with Mathematics categories.
This book introduces best practices in longitudinal data analysis at intermediate level, with a minimum number of formulas without sacrificing depths. It meets the need to understand statistical concepts of longitudinal data analysis by visualizing important techniques instead of using abstract mathematical formulas. Different solutions such as multiple imputation are explained conceptually and consequences of missing observations are clarified using visualization techniques. Key features include the following: Provides datasets and examples online Gives state-of-the-art methods of dealing with missing observations in a non-technical way with a special focus on sensitivity analysis Conceptualises the analysis of comparative (experimental and observational) studies It is the ideal companion for researchers and students in epidemiological, health, and social and behavioral sciences working with longitudinal studies without a mathematical background.
Longitudinal Data Analysis
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Author : Toon Taris
language : en
Publisher: SAGE
Release Date : 2000-11-13
Longitudinal Data Analysis written by Toon Taris and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000-11-13 with Social Science categories.
This accessible introduction to the theory and practice of longitudinal research takes the reader through the strengths and weaknesses of this kind of research, making clear: how to design a longitudinal study; how to collect data most effectively; how to make the best use of statistical techniques; and how to interpret results. Although the book provides a broad overview of the field, the focus is always on the practical issues arising out of longitudinal research. This book supplies the student with all that they need to get started and acts as a manual for dealing with opportunities and pitfalls. It is the ideal primer for this growing area of social research.
Longitudinal Data Analysis
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Author : Garrett Fitzmaurice
language : en
Publisher: CRC Press
Release Date : 2008-08-11
Longitudinal Data Analysis written by Garrett Fitzmaurice and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-08-11 with Mathematics categories.
Although many books currently available describe statistical models and methods for analyzing longitudinal data, they do not highlight connections between various research threads in the statistical literature. Responding to this void, Longitudinal Data Analysis provides a clear, comprehensive, and unified overview of state-of-the-art theory
Preventing And Treating Missing Data In Longitudinal Clinical Trials
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Author : Craig Mallinckrodt
language : en
Publisher:
Release Date : 2013
Preventing And Treating Missing Data In Longitudinal Clinical Trials written by Craig Mallinckrodt and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with categories.
Longitudinal Data Analysis
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Author : Professor Catrien C J H C J H Bijleveld
language : en
Publisher: SAGE
Release Date : 1998-10-26
Longitudinal Data Analysis written by Professor Catrien C J H C J H Bijleveld and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998-10-26 with Social Science categories.
By looking at the processes of change over time - by carrying out longitudinal studies - researchers answer questions about learning, development, educational growth, social change and medical outcomes. However, longitudinal research has many faces. This book examines all the main approaches as well as newer developments (such as structural equation modelling, multilevel modelling and optimal scaling) to enable the reader to gain a thorough understanding of the approach and make appropriate decisions about which technique can be applied to the research problem. Conceptual explanations are used to keep technical terms to a minimum; examples are provided for each approach; issues of design, measurement and significance are considered; and a standard notation is used throughout.
A Mixed Model Approach For Intent To Treat Analysis In Longitudinal Clinical Trials With Missing Values
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Author : Hrishikesh Chakraborty
language : en
Publisher: RTI Press
Release Date : 2009-02-28
A Mixed Model Approach For Intent To Treat Analysis In Longitudinal Clinical Trials With Missing Values written by Hrishikesh Chakraborty and has been published by RTI Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-02-28 with Computers categories.
Missing values and dropouts are common issues in longitudinal studies in all areas of medicine and public health. Intent-to-treat (ITT) analysis has become a widely accepted method for the analysis of controlled clinical trials. In most controlled clinical trials, some patients do not complete their intended followup according to the protocol for a variety of reasons; this problem generates missing values. Missing values lead to concern and confusion in identifying the ITT population, which makes the data analysis more complex and challenging. No adequate strategy exists for ITT analyses of longitudinal controlled clinical trial data with missing values. Several ad hoc strategies for dealing with missing values for an ITT analysis are common in the practice of controlled clinical trials. We performed a detailed investigation based on simulation studies to develop recommendations for this situation. We compared sizes (type I errors) and power between some popular ad hoc approaches and the linear mixed model approach under different missing value scenarios. Our results suggest that, for studies with a high percentage of missing values, the mixed model approach without any ad hoc imputation is more powerful than other options.
Grouping Methods For Informative Missing Data In Longitudinal Studies
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Author : Lei Xu
language : en
Publisher:
Release Date : 2007
Grouping Methods For Informative Missing Data In Longitudinal Studies written by Lei Xu and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with categories.
Missing data are common in longitudinal studies and the probability that an observation is missing may depend on the unobserved outcomes. A special case is that the missingness may depend on the outcomes through random effects representing underlying individual characteristics such as disease process or health awareness. To account for such informative missing data, some special methods have to be applied instead of standard analysis. An existing method referred to ACM method incorporates some summary measures of missing patterns as additional covariates. This dissertation investigates and generalizes another approach by grouping data according to summary measures of missingness patterns. We show how such grouping methods can provide desirable estimators and clarify the differences between the ACM and the grouping methods. Detailed steps for carrying out the grouping methods under various missingness mechanisms are shown and a new imputation method based on grouping is proposed. Simulation studies are conducted to evaluate and compare the performances of new and existing methods. These methods are also applied to an example.
Preventing And Treating Missing Data In Longitudinal Clinical Trials
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Author : Craig H. Mallinckrodt
language : en
Publisher: Cambridge University Press
Release Date : 2013-01-28
Preventing And Treating Missing Data In Longitudinal Clinical Trials written by Craig H. Mallinckrodt and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-01-28 with Medical categories.
Recent decades have brought advances in statistical theory for missing data, which, combined with advances in computing ability, have allowed implementation of a wide array of analyses. In fact, so many methods are available that it can be difficult to ascertain when to use which method. This book focuses on the prevention and treatment of missing data in longitudinal clinical trials. Based on his extensive experience with missing data, the author offers advice on choosing analysis methods and on ways to prevent missing data through appropriate trial design and conduct. He offers a practical guide to key principles and explains analytic methods for the non-statistician using limited statistical notation and jargon. The book's goal is to present a comprehensive strategy for preventing and treating missing data, and to make available the programs used to conduct the analyses of the example dataset.