Clinical Trials In Oncology

Author: Stephanie Green
Editor: CRC Press
ISBN: 1420035304
Size: 19,56 MB
Format: PDF, Mobi
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Studies that are unimpeachably thorough, non-political, unbiased, and properly designed... These are the standards to which everyone in clinical research aspires. Yet, the difficulties in designing trials and interpreting data are subtle and ever present. The new edition of Clinical Trials in Oncology provides a concise, nontechnical, and now thoroughly up-to-date review of methods and issues related to clinical trials. The authors emphasize the importance of proper study design, analysis, and data management and identify the major pitfalls that are seemingly inherent in these processes. This edition includes a new section that describes recent innovations in Phase I designs. Another new section on microarray data examines the challenges presented by massive data sets and describes approaches used to meet those challenges. As always, the authors use clear, lucid prose and a multitude of real-world trials as examples to convey the principles of successful trials without the need for a strong statistics or mathematics background. Although the book focuses on cancer trials, the issues and concepts are important in any clinical setting. Clinical Trials in Oncology, Second Edition works to improve the mutual understanding by clinicians and statisticians of the principles of clinical trials and helps them avoid the many hazards that can jeopardize the success of a trial.

Oncology Nursing In The Ambulatory Setting

Author: Patricia Corcoran Buchsel
Editor: Jones & Bartlett Learning
ISBN: 9780763714741
Size: 10,59 MB
Format: PDF, ePub
Read: 209
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This book provides the very lastest in position statements, and new, forward-thinking in administrative strategies. Addresses fiscal management of outpatient cancer centers, including financial systems models, use of CPT codes, cost effectivness and clinical applications of evidence-based practice guidelines.

Clinical Trials In Oncology Second Edition

Author: Stephanie Green
Editor: Chapman and Hall/CRC
ISBN: 9781584883029
Size: 10,85 MB
Format: PDF, Mobi
Read: 877
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Studies that are unimpeachably thorough, non-political, unbiased, and properly designed... These are the standards to which everyone in clinical research aspires. Yet, the difficulties in designing trials and interpreting data are subtle and ever present. The new edition of Clinical Trials in Oncology provides a concise, nontechnical, and now thoroughly up-to-date review of methods and issues related to clinical trials. The authors emphasize the importance of proper study design, analysis, and data management and identify the major pitfalls that are seemingly inherent in these processes. This edition includes a new section that describes recent innovations in Phase I designs. Another new section on microarray data examines the challenges presented by massive data sets and describes approaches used to meet those challenges. As always, the authors use clear, lucid prose and a multitude of real-world trials as examples to convey the principles of successful trials without the need for a strong statistics or mathematics background. Although the book focuses on cancer trials, the issues and concepts are important in any clinical setting. Clinical Trials in Oncology, Second Edition works to improve the mutual understanding by clinicians and statisticians of the principles of clinical trials and helps them avoid the many hazards that can jeopardize the success of a trial.

Measurement Error

Author: John P. Buonaccorsi
Editor: CRC Press
ISBN: 9781420066586
Size: 19,92 MB
Format: PDF, Kindle
Read: 171
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Over the last 20 years, comprehensive strategies for treating measurement error in complex models and accounting for the use of extra data to estimate measurement error parameters have emerged. Focusing on both established and novel approaches, Measurement Error: Models, Methods, and Applications provides an overview of the main techniques and illustrates their application in various models. It describes the impacts of measurement errors on naive analyses that ignore them and presents ways to correct for them across a variety of statistical models, from simple one-sample problems to regression models to more complex mixed and time series models. The book covers correction methods based on known measurement error parameters, replication, internal or external validation data, and, for some models, instrumental variables. It emphasizes the use of several relatively simple methods, moment corrections, regression calibration, simulation extrapolation (SIMEX), modified estimating equation methods, and likelihood techniques. The author uses SAS-IML and Stata to implement many of the techniques in the examples. Accessible to a broad audience, this book explains how to model measurement error, the effects of ignoring it, and how to correct for it. More applied than most books on measurement error, it describes basic models and methods, their uses in a range of application areas, and the associated terminology.

Design And Analysis Of Quality Of Life Studies In Clinical Trials Second Edition

Author: Diane L. Fairclough
Editor: CRC Press
ISBN: 1420061186
Size: 14,46 MB
Format: PDF, ePub, Docs
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Design Principles and Analysis Techniques for HRQoL Clinical Trials SAS, R, and SPSS examples realistically show how to implement methods Focusing on longitudinal studies, Design and Analysis of Quality of Life Studies in Clinical Trials, Second Edition addresses design and analysis aspects in enough detail so that readers can apply statistical methods, such as mixed effect models, to their own studies. The author illustrates the implementation of the methods using the statistical software packages SAS, SPSS, and R. New to the Second Edition Data sets available for download online, allowing readers to replicate the analyses presented in the text New chapter on testing models that involve moderation and mediation Revised discussions of multiple comparisons procedures that focus on the integration of health-related quality of life (HRQoL) outcomes with other study outcomes using gatekeeper strategies Recent methodological developments for the analysis of trials with missing data New chapter on quality adjusted life-years (QALYs) and QTWiST specific to clinical trials Additional examples of the implementation of basic models and other selected applications in R and SPSS This edition continues to provide practical information for researchers directly involved in the design and analysis of HRQoL studies as well as for those who evaluate the design and interpret the results of HRQoL research. By following the examples in the book, readers will be able to apply the steps to their own trials.

Statistics In Musicology

Author: Jan Beran
Editor: CRC Press
ISBN: 0203496949
Size: 19,11 MB
Format: PDF, Mobi
Read: 938
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Traditionally, statistics and music are not generally associated with each other. However, ...intelligent... music software, computer digitization, and other advanced techniques and technologies have precipitated the need for standard statistical models to answer basic musicological questions. Statistics In Musicology presents an unprecedented introduction to statistical and mathematical methods developed for use in music analysis, music theory, and performance theory. It explores concrete methods for data generation and numerical encoding of musical data and serves as a practical reference for a wide audience, including statisticians, mathematicians, musicologists, and musicians.

Bayesian Analysis For Population Ecology

Author: Ruth King
Editor: Chapman & Hall
ISBN:
Size: 17,66 MB
Format: PDF, Kindle
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Modern Bayesian methods have an important role to play in population ecology. Statistical methods for the analysis of mark-recapture-recovery data on wild animals continue to develop in response to the availability of long-term data sets and advances in animal marking and tracking techniques. Bringing together top experts in the field, this book presents up-to-date Bayesian procedures in an accessible manner, illustrated by a wide range of real examples and complemented by accessible computer programs. The authors include WinBUGS and R code for all of the analyses that are performed in the text.

Bayesian Disease Mapping

Author: Andrew B. Lawson
Editor: CRC Press
ISBN: 1466504811
Size: 15,35 MB
Format: PDF, ePub
Read: 455
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Since the publication of the first edition, many new Bayesian tools and methods have been developed for space-time data analysis, the predictive modeling of health outcomes, and other spatial biostatistical areas. Exploring these new developments, Bayesian Disease Mapping: Hierarchical Modeling in Spatial Epidemiology, Second Edition provides an up-to-date, cohesive account of the full range of Bayesian disease mapping methods and applications. A biostatistics professor and WHO advisor, the author illustrates the use of Bayesian hierarchical modeling in the geographical analysis of disease through a range of real-world datasets. New to the Second Edition Three new chapters on regression and ecological analysis, putative hazard modeling, and disease map surveillance Expanded material on case event modeling and spatiotemporal analysis New and updated examples Two new appendices featuring examples of integrated nested Laplace approximation (INLA) and conditional autoregressive (CAR) models In addition to these new topics, the book covers more conventional areas such as relative risk estimation, clustering, spatial survival analysis, and longitudinal analysis. After an introduction to Bayesian inference, computation, and model assessment, the text focuses on important themes, including disease map reconstruction, cluster detection, regression and ecological analysis, putative hazard modeling, analysis of multiple scales and multiple diseases, spatial survival and longitudinal studies, spatiotemporal methods, and map surveillance. It shows how Bayesian disease mapping can yield significant insights into georeferenced health data. WinBUGS and R are used throughout for data manipulation and simulation.