Nonlinear Models In Medical Statistics
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Nonlinear Models In Medical Statistics
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Author : James K. Lindsey
language : en
Publisher:
Release Date : 2001
Nonlinear Models In Medical Statistics written by James K. Lindsey and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001 with Mathematics categories.
This text provides an introduction to the use of nonlinear models in medical statistics, It is a practical text rather than a theoretical one and assumes a basic knowledge in statistical modelling and of generalized linear models. The book first provides a general introduction to nonlinear models, comparing them to generalized linear models. It describes data handling and formula definition and summarises the principal types of nonlinear regression formulae. there is an emphasis on techniques for non-normal data.Following chapters provide detailed examples of applications in various areas of medicine, epidemiology, clinical trials, quality of life, pharmokinetics, pharmacodynamics, assays and formulations, and molecular genetics.The book concludes with appendicies describing data handling and model formulae in more detail, and given ways of modelling dependencies in repeated measurements, and data for the exercises.
Fitting Models To Biological Data Using Linear And Nonlinear Regression
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Author : Harvey Motulsky
language : en
Publisher: Oxford University Press
Release Date : 2004-05-27
Fitting Models To Biological Data Using Linear And Nonlinear Regression written by Harvey Motulsky and has been published by Oxford University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-05-27 with Mathematics categories.
Most biologists use nonlinear regression more than any other statistical technique, but there are very few places to learn about curve-fitting. This book, by the author of the very successful Intuitive Biostatistics, addresses this relatively focused need of an extraordinarily broad range of scientists.
Nonlinear Models For Repeated Measurement Data
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Author : Marie Davidian
language : en
Publisher: CRC Press
Release Date : 1995-06-01
Nonlinear Models For Repeated Measurement Data written by Marie Davidian and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995-06-01 with Mathematics categories.
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.
Statistical Tools For Nonlinear Regression
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Author : Sylvie Huet
language : en
Publisher: Springer Science & Business Media
Release Date : 2006-04-18
Statistical Tools For Nonlinear Regression written by Sylvie Huet 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 2006-04-18 with Mathematics categories.
Statistical Tools for Nonlinear Regression presents methods for analyzing data. It has been expanded to include binomial, multinomial and Poisson non-linear models. The examples are analyzed with the free software nls2 updated to deal with the new models included in the second edition. The nls2 package is implemented in S-PLUS and R. Several additional tools are included in the package for calculating confidence regions for functions of parameters or calibration intervals, using classical methodology or bootstrap.
Applied Statistics In Agricultural Biological And Environmental Sciences
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Author : Barry Glaz
language : en
Publisher: John Wiley & Sons
Release Date : 2020-01-22
Applied Statistics In Agricultural Biological And Environmental Sciences written by Barry Glaz and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-01-22 with Technology & Engineering categories.
Better experimental design and statistical analysis make for more robust science. A thorough understanding of modern statistical methods can mean the difference between discovering and missing crucial results and conclusions in your research, and can shape the course of your entire research career. With Applied Statistics, Barry Glaz and Kathleen M. Yeater have worked with a team of expert authors to create a comprehensive text for graduate students and practicing scientists in the agricultural, biological, and environmental sciences. The contributors cover fundamental concepts and methodologies of experimental design and analysis, and also delve into advanced statistical topics, all explored by analyzing real agronomic data with practical and creative approaches using available software tools. IN PRESS! This book is being published according to the “Just Published” model, with more chapters to be published online as they are completed.
Numerical Methods For Nonlinear Estimating Equations
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Author : Christopher G. Small
language : en
Publisher: OUP Oxford
Release Date : 2003-10-02
Numerical Methods For Nonlinear Estimating Equations written by Christopher G. Small and has been published by OUP Oxford this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003-10-02 with Mathematics categories.
Nonlinearity arises in statistical inference in various ways, with varying degrees of severity, as an obstacle to statistical analysis. More entrenched forms of nonlinearity often require intensive numerical methods to construct estimators, and the use of root search algorithms, or one-step estimators, is a standard method of solution. This book provides a comprehensive study of nonlinear estimating equations and artificial likelihoods for statistical inference. It provides extensive coverage and comparison of hill climbing algorithms, which, when started at points of nonconcavity often have very poor convergence properties, and for additional flexibility proposes a number of modifications to the standard methods for solving these algorithms. The book also extends beyond simple root search algorithms to include a discussion of the testing of roots for consistency, and the modification of available estimating functions to provide greater stability in inference. A variety of examples from practical applications are included to illustrate the problems and possibilities thus making this text ideal for the research statistician and graduate student. This is the latest in the well-established and authoritative Oxford Statistical Science Series, which includes texts and monographs covering many topics of current research interest in pure and applied statistics. Each title has an original slant even if the material included is not specifically original. The authors are leading researchers and the topics covered will be of interest to all professional statisticians, whether they be in industry, government department or research institute. Other books in the series include 23. W.J.Krzanowski: Principles of multivariate analysis: a user's perspective updated edition 24. J.Durbin and S.J.Koopman: Time series analysis by State Space Models 25. Peter J. Diggle, Patrick Heagerty, Kung-Yee Liang, Scott L. Zeger: Analysis of Longitudinal Data 2/e 26. J.K. Lindsey: Nonlinear Models in Medical Statistics 27. Peter J. Green, Nils L. Hjort & Sylvia Richardson: Highly Structured Stochastic Systems 28. Margaret S. Pepe: The Statistical Evaluation of Medical Tests for Classification and Prediction
Principles Of Multivariate Analysis
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Author : W. J. Krzanowski
language : en
Publisher: Oxford University Press
Release Date : 2000-09-28
Principles Of Multivariate Analysis written by W. J. Krzanowski and has been published by Oxford University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000-09-28 with Mathematics categories.
Multivariate analysis is necessary whenever more than one characteristic is observed on each individual under study. Applications arise in very many areas of study. This book provides a comprehensive introduction to available techniques for analysing date of this form, written in a style that should appeal to non-specialists as well as to statisticians. In particular, geometric intuition is emphasized in preference to algebraic manipulation wherever possible. The new edition includes a survey of the most recent developments in the subject.
Analysis Of Longitudinal Data
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Author : Peter Diggle
language : en
Publisher: OUP Oxford
Release Date : 2013-03-14
Analysis Of Longitudinal Data written by Peter Diggle and has been published by OUP Oxford this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-03-14 with Mathematics categories.
The first edition of Analysis for Longitudinal Data has become a classic. Describing the statistical models and methods for the analysis of longitudinal data, it covers both the underlying statistical theory of each method, and its application to a range of examples from the agricultural and biomedical sciences. The main topics discussed are design issues, exploratory methods of analysis, linear models for continuous data, general linear models for discrete data, and models and methods for handling data and missing values. Under each heading, worked examples are presented in parallel with the methodological development, and sufficient detail is given to enable the reader to reproduce the author's results using the data-sets as an appendix. This second edition, published for the first time in paperback, provides a thorough and expanded revision of this important text. It includes two new chapters; the first discusses fully parametric models for discrete repeated measures data, and the second explores statistical models for time-dependent predictors.
Time Series Analysis By State Space Methods
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Author : James Durbin
language : en
Publisher: OUP Oxford
Release Date : 2012-05-03
Time Series Analysis By State Space Methods written by James Durbin and has been published by OUP Oxford this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-05-03 with Business & Economics categories.
This new edition updates Durbin & Koopman's important text on the state space approach to time series analysis. The distinguishing feature of state space time series models is that observations are regarded as made up of distinct components such as trend, seasonal, regression elements and disturbance terms, each of which is modelled separately. The techniques that emerge from this approach are very flexible and are capable of handling a much wider range of problems than the main analytical system currently in use for time series analysis, the Box-Jenkins ARIMA system. Additions to this second edition include the filtering of nonlinear and non-Gaussian series. Part I of the book obtains the mean and variance of the state, of a variable intended to measure the effect of an interaction and of regression coefficients, in terms of the observations. Part II extends the treatment to nonlinear and non-normal models. For these, analytical solutions are not available so methods are based on simulation.
Research Awards Index
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Author :
language : en
Publisher:
Release Date : 1976
Research Awards Index written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1976 with Medicine categories.