Peter M. Fayers / David Machin
(both of MRC Cancer Trials Office, UK)
Quality of Life
Assessment, Analysis, and Interpretation
ISBN: 0-471-96861-7
Hardcover
Pages: 416
Published: Apr 2000
Copyright: 2000
Quality of life assessments have become especially important to those designing medicines to treat the ill. Developing drugs free of troublesome side effects is a major priority for pharmaceutical companies. Assessing and analyzing quality of life data is quickly becoming part of clinical trials procedure, and is even mandatory for acquiring major research grants. Written by two pioneers in the quality of life field, this is the first book to detail extensively the guidelines for assessing and analyzing quality of life data.
Table of Contents
Principles of Measurement Scales.
DEVELOPING AND TESTING QUESTIONNAIRES.
Scores and Measurements: Validity, Reliability, Sensitivity.
Multi-item Scales.
Factor Analysis.
Item Response Theory and Differential Item Functioning.
Questionnaire Development and Scoring.
ANALYSIS OF QoL DATA.
Cross-sectional Analysis.
Exploring Longitudinal Data.
Modelling Longitudinal Data.
Missing Data.
Quality-adjusted Survival.
PRACTICAL ASPECTS AND CLINICAL INTERPRETATION.
Clinical Trials.
Sample Sizes.
Practical and Reporting Issues.
Clinical Interpretation.
Appendices.
References.
Index.
Mark Ainsworth (Univ. of Leicester, UK)
J. Tinsley Oden (Univ. of Texas, Austin, Texas)
A Posterior Error Estimation in Finite Element Analysis
ISBN: 0-471-29411-X
Hardcover
Pages: 264
Copyright: 2000
An up-to-date, one-stop reference-complete with applications
This volume presents the most up-to-date information available on a posteriori error estimation for finite element approximation in mechanics and mathematics. It emphasizes methods for elliptic boundary value problems and includes applications to incompressible flow and nonlinear problems.
Recent years have seen an explosion in the study of a posteriori error estimators due to their remarkable influence on improving both accuracy and reliability in scientific computing. In an effort to provide an accessible source, the authors have sought to present key ideas and common principles on a sound mathematical footing.
Topics covered in this timely reference include:
Implicit and explicit a posteriori error estimators
Recovery-based error estimators
Estimators, indicators, and hierarchic bases
The equilibrated residual method
Methodology for the comparison of estimators
Estimation of errors in quantities of interest
A Posteriori Error Estimation in Finite Element Analysis is a lucid and convenient resource for researchers in almost any field of finite element methods, and for applied mathematicians and engineers who have an interest in error estimation and/or finite elements.
Subject: Mathematics / Mathematics Special Topics
Series Title: Pure and Applied Mathematics: A Wiley-Interscience Series of Texts, Monographs and Tracts
Noga Alon (Tel Aviv Univ., Israel)
Joel Spencer (Courant Institute, New York Univ., New York, NY)
The Probabilistic Method, 2nd Edition
ISBN: 0-471-37046-0
Hardcover
Price: in press
Pages: 328
Copyright: 2000
The leading reference on probabilistic methods in combinatorics-now expanded and updated
When it was first published in 1991, The Probabilistic Method became instantly the standard reference on one of the most powerful and widely used tools in combinatorics. Still without competition nearly a decade later, this new edition brings you up to speed on recent developments, while adding useful exercises and over 30% new material. It continues to emphasize the basic elements of the methodology, discussing in a remarkably clear and informal style both algorithmic and classical methods as well as modern applications.
The Probabilistic Method, Second Edition begins with basic techniques that use expectation and variance, as well as the more recent martingales and correlation inequalities, then explores areas where probabilistic techniques proved successful, including discrepancy and random graphs as well as cutting-edge topics in theoretical computer science. A series of proofs, or "probabilistic lenses," are interspersed throughout the book, offering added insight into the application of the probabilistic approach. New and revised coverage
includes:
Several improved as well as new results
A continuous approach to discrete probabilistic problems
Talagrand’s Inequality and other novel concentration results
A discussion of the connection between discrepancy and VC-dimension
Several combinatorial applications of the entropy function and its properties
A new section on the life and work of Paul ErdösThe developer of the probabilistic method
Subject: Mathematics / Discrete Mathematics
Series Title: Wiley-Interscience Series in Discrete Mathematics
Olive Jean Dunn (Professor Emeritus, Univ. of California, Los Angeles)
Virginia Ann Clark (Professor Emeritus, Univ. of California, Los Angeles)
Basic Statistics: A Primer for Biomedical Sciences, 3rd Edition
ISBN: 0-471-35422-8
Hardcover
Pages: 256
Copyright: 2000
This volume, like its predecessors, may serve as a textbook for a single semester course in statistics for students in the biomedical field, or as a handy reference book for practicing biostatisticians. The mathematical level is deliberately kept to a minimum, and the chapters are written in a particularly clear and concise fashion. The clearness of the writing is based on the authors' teaching experiences with beginning students, their firm grasps of statistics, and their sense of what to include and what not to include in a book
of this type. The original intent of the inclusion of short chapters was to encourage student completion and macroscopic development. The spirit of that approach has been maintained in this edition. To address today's biostatistical approaches, an emphasis has now been placed on the greater use of data analysis through computer manipulation.
Table of Contents
Populations and Samples.
Frequency Tables and Their Graphs.
Measures of Location and Variability.
The Normal Distribution.
Estimation of Population Means: Confidence Intervals.
Tests of Hypotheses on Population Means.
Categorical Data: Proportions.
Categorical Data: Analysis Of Two-Way Frequency Tables.
Variances: Estimation and Tests.
Regression and Correlation.
Introduction to Survival Analysis.
Appendices.
Index.
Subject: Statistics / Applied Probability & Statistics / Biostatistics
Series Title: Wiley Series in Probability and Statistics: Texts and References Section
O. Carruth McGehee (Louisiana State Univ.)
An Introduction to Complex Analysis
ISBN: 0-471-33233-X
Hardcover
Pages: 456
Copyright: 2000
Complex analysis is a fundamental branch of mathematics with important applications in many areas of the physical sciences. This book provides an up-to-date treatment of the subject.
Table of Contents
Preliminaries.
Basic Tools.
The Cauchy Theory.
The Residue Calculus.
Boundary Value Problems.
Lagniappe.
References.
Index.
Subject: Mathematics / Algebra / Complex and Functional Analysis
Richard L. Valliant (WESTAT Corp, Rockville, Maryland)
Alan H. Dorfman (Bureau of Labor Statistics, Washington, D.C.)
Richard M. Royall (The Johns Hopkins Univ., Baltimore, Maryland)
Finite Population Sampling and Inference
A Prediction Approach
ISBN: 0-471-29341-5
Hardcover
Pages: 536
Copyright: 2000
Complete coverage of the prediction approach to survey sampling in a single resource
Prediction theory has been extremely influential in survey sampling for nearly three decades, yet research findings on this model-based approach are scattered in disparate areas of the statistical literature. Finite Population Sampling and Inference: A Prediction Approach presents for the first time a unified treatment of sample design and estimation for finite populations from a prediction point of view, providing readers with access to a wealth of theoretical results, including many new results and, a variety of practical applications.
Geared to theoretical statisticians and practitioners alike, the book discusses all topics from the ground up and clearly explains the relation of the prediction approach to the traditional design-based randomization approach. Key features include:
Special emphasis on linking survey sampling to mainstream statistics through extensive use of general linear models A liberal use of simulation studies, numerical examples, and exercises illustrating theoretical results
Numerous statistical graphics showing simulation results and properties of estimates
A library of S-Plus computer functions plus six real populations, available via ftp
Over 260 references to finite population sampling, linear models, and other relevant literature
Table of Contents
Introduction to Prediction Theory.
Prediction Theory under the General Linear Model.
Bias-Robustness.
Robustness and Efficiency.
Variance Estimation.
Stratified Populations.
Models with Qualitative Auxiliaries.
Clustered Populations.
Robust Variance Estimation in Two-Stage Sampling.
Alternative Variance Estimation Methods.
Special Topics and Open Questions.
Appendices.
References.
Indexes.
Subject: Statistics / Survey Research Methods and Sampling
Series Title: Wiley Series in Probability and Statistics: Survey Methodology Section