Analysing Survival Data from Clinical Trials and Observational Studies

Analysing Survival Data from Clinical Trials and Observational Studies PDF Author: Ettore Marubini
Publisher: John Wiley & Sons
ISBN: 9780470093412
Category : Mathematics
Languages : en
Pages : 436

Get Book Here

Book Description
A practical guide to methods of survival analysis for medical researchers with limited statistical experience. Methods and techniques described range from descriptive and exploratory analysis to multivariate regression methods. Uses illustrative data from actual clinical trials and observational studies to describe methods of analysing and reporting results. Also reviews the features and performance of statistical software available for applying the methods of analysis discussed.

Analysing Survival Data from Clinical Trials and Observational Studies

Analysing Survival Data from Clinical Trials and Observational Studies PDF Author: Ettore Marubini
Publisher: John Wiley & Sons
ISBN: 9780470093412
Category : Mathematics
Languages : en
Pages : 436

Get Book Here

Book Description
A practical guide to methods of survival analysis for medical researchers with limited statistical experience. Methods and techniques described range from descriptive and exploratory analysis to multivariate regression methods. Uses illustrative data from actual clinical trials and observational studies to describe methods of analysing and reporting results. Also reviews the features and performance of statistical software available for applying the methods of analysis discussed.

Small Clinical Trials

Small Clinical Trials PDF Author: Institute of Medicine
Publisher: National Academies Press
ISBN: 0309171148
Category : Medical
Languages : en
Pages : 221

Get Book Here

Book Description
Clinical trials are used to elucidate the most appropriate preventive, diagnostic, or treatment options for individuals with a given medical condition. Perhaps the most essential feature of a clinical trial is that it aims to use results based on a limited sample of research participants to see if the intervention is safe and effective or if it is comparable to a comparison treatment. Sample size is a crucial component of any clinical trial. A trial with a small number of research participants is more prone to variability and carries a considerable risk of failing to demonstrate the effectiveness of a given intervention when one really is present. This may occur in phase I (safety and pharmacologic profiles), II (pilot efficacy evaluation), and III (extensive assessment of safety and efficacy) trials. Although phase I and II studies may have smaller sample sizes, they usually have adequate statistical power, which is the committee's definition of a "large" trial. Sometimes a trial with eight participants may have adequate statistical power, statistical power being the probability of rejecting the null hypothesis when the hypothesis is false. Small Clinical Trials assesses the current methodologies and the appropriate situations for the conduct of clinical trials with small sample sizes. This report assesses the published literature on various strategies such as (1) meta-analysis to combine disparate information from several studies including Bayesian techniques as in the confidence profile method and (2) other alternatives such as assessing therapeutic results in a single treated population (e.g., astronauts) by sequentially measuring whether the intervention is falling above or below a preestablished probability outcome range and meeting predesigned specifications as opposed to incremental improvement.

Analysing Survival Data from Clinical Trials and Observational Studies

Analysing Survival Data from Clinical Trials and Observational Studies PDF Author: Ettore Marubini
Publisher: John Wiley & Sons
ISBN: 0470093412
Category : Mathematics
Languages : en
Pages : 435

Get Book Here

Book Description
A practical guide to methods of survival analysis for medical researchers with limited statistical experience. Methods and techniques described range from descriptive and exploratory analysis to multivariate regression methods. Uses illustrative data from actual clinical trials and observational studies to describe methods of analysing and reporting results. Also reviews the features and performance of statistical software available for applying the methods of analysis discussed.

Developing a Protocol for Observational Comparative Effectiveness Research: A User's Guide

Developing a Protocol for Observational Comparative Effectiveness Research: A User's Guide PDF Author: Agency for Health Care Research and Quality (U.S.)
Publisher: Government Printing Office
ISBN: 1587634236
Category : Medical
Languages : en
Pages : 236

Get Book Here

Book Description
This User’s Guide is a resource for investigators and stakeholders who develop and review observational comparative effectiveness research protocols. It explains how to (1) identify key considerations and best practices for research design; (2) build a protocol based on these standards and best practices; and (3) judge the adequacy and completeness of a protocol. Eleven chapters cover all aspects of research design, including: developing study objectives, defining and refining study questions, addressing the heterogeneity of treatment effect, characterizing exposure, selecting a comparator, defining and measuring outcomes, and identifying optimal data sources. Checklists of guidance and key considerations for protocols are provided at the end of each chapter. The User’s Guide was created by researchers affiliated with AHRQ’s Effective Health Care Program, particularly those who participated in AHRQ’s DEcIDE (Developing Evidence to Inform Decisions About Effectiveness) program. Chapters were subject to multiple internal and external independent reviews. More more information, please consult the Agency website: www.effectivehealthcare.ahrq.gov)

Applied Survival Analysis Using R

Applied Survival Analysis Using R PDF Author: Dirk F. Moore
Publisher: Springer
ISBN: 3319312456
Category : Medical
Languages : en
Pages : 245

Get Book Here

Book Description
Applied Survival Analysis Using R covers the main principles of survival analysis, gives examples of how it is applied, and teaches how to put those principles to use to analyze data using R as a vehicle. Survival data, where the primary outcome is time to a specific event, arise in many areas of biomedical research, including clinical trials, epidemiological studies, and studies of animals. Many survival methods are extensions of techniques used in linear regression and categorical data, while other aspects of this field are unique to survival data. This text employs numerous actual examples to illustrate survival curve estimation, comparison of survivals of different groups, proper accounting for censoring and truncation, model variable selection, and residual analysis. Because explaining survival analysis requires more advanced mathematics than many other statistical topics, this book is organized with basic concepts and most frequently used procedures covered in earlier chapters, with more advanced topics near the end and in the appendices. A background in basic linear regression and categorical data analysis, as well as a basic knowledge of calculus and the R system, will help the reader to fully appreciate the information presented. Examples are simple and straightforward while still illustrating key points, shedding light on the application of survival analysis in a way that is useful for graduate students, researchers, and practitioners in biostatistics.

Survival Analysis

Survival Analysis PDF Author: John P. Klein
Publisher: Springer Science & Business Media
ISBN: 1475727283
Category : Medical
Languages : en
Pages : 508

Get Book Here

Book Description
Making complex methods more accessible to applied researchers without an advanced mathematical background, the authors present the essence of new techniques available, as well as classical techniques, and apply them to data. Practical suggestions for implementing the various methods are set off in a series of practical notes at the end of each section, while technical details of the derivation of the techniques are sketched in the technical notes. This book will thus be useful for investigators who need to analyse censored or truncated life time data, and as a textbook for a graduate course in survival analysis, the only prerequisite being a standard course in statistical methodology.

Analysis of Observational Health Care Data Using SAS

Analysis of Observational Health Care Data Using SAS PDF Author: Douglas E. Faries
Publisher: SAS Press
ISBN: 9781607642275
Category : Medical care
Languages : en
Pages : 0

Get Book Here

Book Description
This book guides researchers in performing and presenting high-quality analyses of all kinds of non-randomized studies, including analyses of observational studies, claims database analyses, assessment of registry data, survey data, pharmaco-economic data, and many more applications. The text is sufficiently detailed to provide not only general guidance, but to help the researcher through all of the standard issues that arise in such analyses. Just enough theory is included to allow the reader to understand the pros and cons of alternative approaches and when to use each method. The numerous contributors to this book illustrate, via real-world numerical examples and SAS code, appropriate implementations of alternative methods. The end result is that researchers will learn how to present high-quality and transparent analyses that will lead to fair and objective decisions from observational data. This book is part of the SAS Press program.

Survival and Event History Analysis

Survival and Event History Analysis PDF Author: Odd Aalen
Publisher: Springer Science & Business Media
ISBN: 038768560X
Category : Mathematics
Languages : en
Pages : 550

Get Book Here

Book Description
The aim of this book is to bridge the gap between standard textbook models and a range of models where the dynamic structure of the data manifests itself fully. The common denominator of such models is stochastic processes. The authors show how counting processes, martingales, and stochastic integrals fit very nicely with censored data. Beginning with standard analyses such as Kaplan-Meier plots and Cox regression, the presentation progresses to the additive hazard model and recurrent event data. Stochastic processes are also used as natural models for individual frailty; they allow sensible interpretations of a number of surprising artifacts seen in population data. The stochastic process framework is naturally connected to causality. The authors show how dynamic path analyses can incorporate many modern causality ideas in a framework that takes the time aspect seriously. To make the material accessible to the reader, a large number of practical examples, mainly from medicine, are developed in detail. Stochastic processes are introduced in an intuitive and non-technical manner. The book is aimed at investigators who use event history methods and want a better understanding of the statistical concepts. It is suitable as a textbook for graduate courses in statistics and biostatistics.

Modelling Survival Data in Medical Research

Modelling Survival Data in Medical Research PDF Author: David Collett
Publisher:
ISBN: 9780429258374
Category : Clinical trials
Languages : en
Pages : 368

Get Book Here

Book Description
Data collected on the time to an event-such as the death of a patient in a medical study-is known as survival data. The methods for analyzing survival data can also be used to analyze data on the time to events such as the recurrence of a disease or relief from symptoms. Modelling Survival Data in Medical Research begins with an introduction to survival analysis and a description of four studies in which survival data was obtained. These and other data sets are then used to illustrate the techniques presented in the following chapters, including the Cox and Weibull proportional hazards models; accelerated failure time models; models with time-dependent variables; interval-censored survival data; model checking; and use of statistical packages. Designed for statisticians in the pharmaceutical industry and medical research institutes, and for numerate scientists and clinicians analyzing their own data sets, this book also meets the need for an intermediate text which emphasizes the application of the methodology to survival data arising from medical studies.

Survival Analysis

Survival Analysis PDF Author: David Machin
Publisher: John Wiley & Sons
ISBN: 0470870419
Category : Medical
Languages : en
Pages : 278

Get Book Here

Book Description
Well received in its first edition, Survival Analysis: A Practical Approach is completely revised to provide an accessible and practical guide to survival analysis techniques in diverse environments. Illustrated with many authentic examples, the book introduces basic statistical concepts and methods to construct survival curves, later developing them to encompass more specialised and complex models. During the years since the first edition there have been several new topics that have come to the fore and many new applications. Parallel developments in computer software programmes, used to implement these methodologies, are relied upon throughout the text to bring it up to date.