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Nonlinear Models for Repeated Measurement Data by Marie Davidian Pdf
Nonlinear measurement data arise in a wide variety of biological and biomedical applications, such as longitudinal clinical trials, studies of drug kinetics and growth, and the analysis of assay and laboratory data. Nonlinear Models for Repeated Measurement Data provides the first unified development of methods and models for data of this type, with a detailed treatment of inference for the nonlinear mixed effects and its extensions. A particular strength of the book is the inclusion of several detailed case studies from the areas of population pharmacokinetics and pharmacodynamics, immunoassay and bioassay development and the analysis of growth curves.
Nonlinear Models for Repeated Measurement Data by Marie Davidian Pdf
Nonlinear measurement data arise in a wide variety of biological and biomedical applications, such as longitudinal clinical trials, studies of drug kinetics and growth, and the analysis of assay and laboratory data. Nonlinear Models for Repeated Measurement Data provides the first unified development of methods and models for data of this type, with a detailed treatment of inference for the nonlinear mixed effects and its extensions. A particular strength of the book is the inclusion of several detailed case studies from the areas of population pharmacokinetics and pharmacodynamics, immunoassay and bioassay development and the analysis of growth curves.
Linear and Nonlinear Models for the Analysis of Repeated Measurements by Edward Vonesh,Vernon M. Chinchilli Pdf
Integrates the latest theory, methodology and applications related to the design and analysis of repeated measurement. The text covers a broad range of topics, including the analysis of repeated measures design, general crossover designs, and linear and nonlinear regression models. It also contains a 3.5 IBM compatible disk, with software to implement immediately the techniques.
Linear and Nonlinear Models for the Analysis of Repeated Measurements by Edward Vonesh,Vernon M Chinchilli Pdf
Integrates the latest theory, methodology and applications related to the design and analysis of repeated measurement. The text covers a broad range of topics, including the analysis of repeated measures design, general crossover designs, and linear and nonlinear regression models. It also contains a 3.5 IBM compatible disk, with software to implement immediately the techniques.
Linear and Nonlinear Models for the Analysis of Repeated Measurements by Edward Vonesh,Vernon M. Chinchilli Pdf
Integrates the latest theory, methodology and applications related to the design and analysis of repeated measurement. The text covers a broad range of topics, including the analysis of repeated measures design, general crossover designs, and linear and nonlinear regression models. It also contains a 3.5 IBM compatible disk, with software to implem
Measurement Error in Nonlinear Models by Raymond J. Carroll,David Ruppert,Leonard A. Stefanski,Ciprian M. Crainiceanu Pdf
It's been over a decade since the first edition of Measurement Error in Nonlinear Models splashed onto the scene, and research in the field has certainly not cooled in the interim. In fact, quite the opposite has occurred. As a result, Measurement Error in Nonlinear Models: A Modern Perspective, Second Edition has been revamped and ex
Mixed Effects Models for Complex Data by Lang Wu Pdf
Although standard mixed effects models are useful in a range of studies, other approaches must often be used in correlation with them when studying complex or incomplete data. Mixed Effects Models for Complex Data discusses commonly used mixed effects models and presents appropriate approaches to address dropouts, missing data, measurement errors, censoring, and outliers. For each class of mixed effects model, the author reviews the corresponding class of regression model for cross-sectional data. An overview of general models and methods, along with motivating examples After presenting real data examples and outlining general approaches to the analysis of longitudinal/clustered data and incomplete data, the book introduces linear mixed effects (LME) models, generalized linear mixed models (GLMMs), nonlinear mixed effects (NLME) models, and semiparametric and nonparametric mixed effects models. It also includes general approaches for the analysis of complex data with missing values, measurement errors, censoring, and outliers. Self-contained coverage of specific topics Subsequent chapters delve more deeply into missing data problems, covariate measurement errors, and censored responses in mixed effects models. Focusing on incomplete data, the book also covers survival and frailty models, joint models of survival and longitudinal data, robust methods for mixed effects models, marginal generalized estimating equation (GEE) models for longitudinal or clustered data, and Bayesian methods for mixed effects models. Background material In the appendix, the author provides background information, such as likelihood theory, the Gibbs sampler, rejection and importance sampling methods, numerical integration methods, optimization methods, bootstrap, and matrix algebra. Failure to properly address missing data, measurement errors, and other issues in statistical analyses can lead to severely biased or misleading results. This book explores the biases that arise when naïve methods are used and shows which approaches should be used to achieve accurate results in longitudinal data analysis.
Multilevel Modeling Methods with Introductory and Advanced Applications by Ann A. O'Connell,D. Betsy McCoach,Bethany A. Bell Pdf
Multilevel Modeling Methods with Introductory and Advanced Applications provides a cogent and comprehensive introduction to the area of multilevel modeling for methodological and applied researchers as well as advanced graduate students. The book is designed to be able to serve as a textbook for a one or two semester course in multilevel modeling. The topics of the seventeen chapters range from basic to advanced, yet each chapter is designed to be able to stand alone as an instructional unit on its respective topic, with an emphasis on application and interpretation. In addition to covering foundational topics on the use of multilevel models for organizational and longitudinal research, the book includes chapters on more advanced extensions and applications, such as cross-classified random effects models, non-linear growth models, mixed effects location scale models, logistic, ordinal, and Poisson models, and multilevel mediation. In addition, the volume includes chapters addressing some of the most important design and analytic issues including missing data, power analyses, causal inference, model fit, and measurement issues. Finally, the volume includes chapters addressing special topics such as using large-scale complex sample datasets, and reporting the results of multilevel designs. Each chapter contains a section called Try This!, which poses a structured data problem for the reader. We have linked our book to a website (http://modeling.uconn.edu) containing data for the Try This! section, creating an opportunity for readers to learn by doing. The inclusion of the Try This! problems, data, and sample code eases the burden for instructors, who must continually search for class examples and homework problems. In addition, each chapter provides recommendations for additional methodological and applied readings.
Methods and Applications of Longitudinal Data Analysis by Xian Liu Pdf
Methods and Applications of Longitudinal Data Analysis describes methods for the analysis of longitudinal data in the medical, biological and behavioral sciences. It introduces basic concepts and functions including a variety of regression models, and their practical applications across many areas of research. Statistical procedures featured within the text include: descriptive methods for delineating trends over time linear mixed regression models with both fixed and random effects covariance pattern models on correlated errors generalized estimating equations nonlinear regression models for categorical repeated measurements techniques for analyzing longitudinal data with non-ignorable missing observations Emphasis is given to applications of these methods, using substantial empirical illustrations, designed to help users of statistics better analyze and understand longitudinal data. Methods and Applications of Longitudinal Data Analysis equips both graduate students and professionals to confidently apply longitudinal data analysis to their particular discipline. It also provides a valuable reference source for applied statisticians, demographers and other quantitative methodologists. From novice to professional: this book starts with the introduction of basic models and ends with the description of some of the most advanced models in longitudinal data analysis Enables students to select the correct statistical methods to apply to their longitudinal data and avoid the pitfalls associated with incorrect selection Identifies the limitations of classical repeated measures models and describes newly developed techniques, along with real-world examples.
Applied Data Analytic Techniques For Turning Points Research by Patricia Cohen Pdf
This innovative volume demonstrates the use of a range of statistical approaches that examine "turning points" (a change in direction, magnitude, or meaning) in real data. Analytic techniques are illustrated with real longitudinal data from a variety of fields. As such the book will appeal to a variety of researchers including: Developmental researchers interested in identifying factors precipitating turning points at various life stages. Medical or substance abuse researchers looking for turning points in disease or recovery. Social researchers interested in estimating the effects of life experiences on subsequent behavioral changes. Interpersonal behavior researchers looking to identify turning points in relationships. Brain researchers needing to discriminate the onset of an experimentally produced process in a participant. The book opens with the goals and theoretical considerations in defining turning points. An overview of the methods presented in subsequent chapters is then provided. Chapter goals include discriminating "local" from long-term effects, identifying variables altering the connection between trajectories at different life stages, locating non-normative turning points, coping with practical distributional problems in trajectory analyses, and changes in the meaning and connections between variables in the transition to adulthood. From an applied perspective, the book explores such topics as antisocial/aggressive trajectories at different life stages, the impact of imprisonment on criminal behavior, family contact trajectories in the transition to adulthood, sustained effects of substance abuse, alternative models of bereavement, and identifying brain changes associated with the onset of a new brain process. Ideal for advanced students and researchers interested in identifying significant change in data in a variety of fields including psychology, medicine, education, political science, criminology, and sociology.
Pharmacokinetics and Toxicokinetics by Mehdi Boroujerdi Pdf
Pharmacokinetics and Toxicokinetics provides an overview of pharmacokinetics and toxicokinetics in a comprehensible, interrelated, and applied manner. It integrates the principles held in common by both fields through a logical and systematic approach. The book presents mathematical descriptions of physiological processes employed in different appr
Measurement Error in Nonlinear Models by Raymond J. Carroll,David Ruppert,Leonard A. Stefanski,Ciprian M. Crainiceanu Pdf
It’s been over a decade since the first edition of Measurement Error in Nonlinear Models splashed onto the scene, and research in the field has certainly not cooled in the interim. In fact, quite the opposite has occurred. As a result, Measurement Error in Nonlinear Models: A Modern Perspective, Second Edition has been revamped and extensively updated to offer the most comprehensive and up-to-date survey of measurement error models currently available. What’s new in the Second Edition? · Greatly expanded discussion and applications of Bayesian computation via Markov Chain Monte Carlo techniques · A new chapter on longitudinal data and mixed models · A thoroughly revised chapter on nonparametric regression and density estimation · A totally new chapter on semiparametric regression · Survival analysis expanded into its own separate chapter · Completely rewritten chapter on score functions · Many more examples and illustrative graphs · Unique data sets compiled and made available online In addition, the authors expanded the background material in Appendix A and integrated the technical material from chapter appendices into a new Appendix B for convenient navigation. Regardless of your field, if you’re looking for the most extensive discussion and review of measurement error models, then Measurement Error in Nonlinear Models: A Modern Perspective, Second Edition is your ideal source.
Longitudinal Data Analysis by Garrett Fitzmaurice,Marie Davidian,Geert Verbeke,Geert Molenberghs Pdf
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
