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.

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.

Hugely popular textbook on survival analysis for graduate students of statistics and biostatistics, mainly due to its accessibility and breadth of examples. This is a standard course on graduate programs in biostatistics and statistics, and this is one of the most popular textbooks. Updated with modern methods covering Bayesian survival analysis, joint models, and more.

The explanation and implementation of statistical methods for the medical researcher or statistician remains an integral part of modern medical research. This book explains the use of experimental and analytical biostatistics systems. Its accessible style allows it to be used by the non-mathematician as a fundamental component of successful research. Since the third edition, there have been many developments in statistical techniques. The fourth edition provides the medical statistician with an accessible guide to these techniques and to reflect the extent of their usage in medical research. The new edition takes a much more comprehensive approach to its subject. There has been a radical reorganization of the text to improve the continuity and cohesion of the presentation and to extend the scope by covering many new ideas now being introduced into the analysis of medical research data. The authors have tried to maintain the modest level of mathematical exposition that characterized the earlier editions, essentially confining the mathematics to the statement of algebraic formulae rather than pursuing mathematical proofs. Received the Highly Commended Certificate in the Public Health Category of the 2002 BMA Books Competition.

Classic biostatistics, a branch of statistical science, has as its main focus the applications of statistics in public health, the life sciences, and the pharmaceutical industry. Modern biostatistics, beyond just a simple application of statistics, is a confluence of statistics and knowledge of multiple intertwined fields. The application demands, the advancements in computer technology, and the rapid growth of life science data (e.g., genomics data) have promoted the formation of modern biostatistics. There are at least three characteristics of modern biostatistics: (1) in-depth engagement in the application fields that require penetration of knowledge across several fields, (2) high-level complexity of data because they are longitudinal, incomplete, or latent because they are heterogeneous due to a mixture of data or experiment types, because of high-dimensionality, which may make meaningful reduction impossible, or because of extremely small or large size; and (3) dynamics, the speed of development in methodology and analyses, has to match the fast growth of data with a constantly changing face. This book is written for researchers, biostatisticians/statisticians, and scientists who are interested in quantitative analyses. The goal is to introduce modern methods in biostatistics and help researchers and students quickly grasp key concepts and methods. Many methods can solve the same problem and many problems can be solved by the same method, which becomes apparent when those topics are discussed in this single volume.

Provides timely applications, modifications, and extensions of experimental designs for a variety of disciplines Design and Analysis of Experiments, Volume 3: Special Designs and Applications continues building upon the philosophical foundations of experimental design by providing important, modern applications of experimental design to the many fields that utilize them. The book also presents optimal and efficient designs for practice and covers key topics in current statistical research. Featuring contributions from leading researchers and academics, the book demonstrates how the presented concepts are used across various fields from genetics and medicinal and pharmaceutical research to manufacturing, engineering, and national security. Each chapter includes an introduction followed by the historical background as well as in-depth procedures that aid in the construction and analysis of the discussed designs. Topical coverage includes: Genetic cross experiments, microarray experiments, and variety trials Clinical trials, group-sequential designs, and adaptive designs Fractional factorial and search, choice, and optimal designs for generalized linear models Computer experiments with applications to homeland security Robust parameter designs and split-plot type response surface designs Analysis of directional data experiments Throughout the book, illustrative and numerical examples utilize SAS®, JMP®, and R software programs to demonstrate the discussed techniques. Related data sets and software applications are available on the book's related FTP site. Design and Analysis of Experiments, Volume 3 is an ideal textbook for graduate courses in experimental design and also serves as a practical, hands-on reference for statisticians and researchers across a wide array of subject areas, including biological sciences, engineering, medicine, and business.

"Reflecting the interrelationship with diverse fields, topics range from health psychology to health economics, ethics, and biostatistics. Some articles desribe underlying biostatistical concepts-from measures of central tendency, to kappa, to the Pearson correlation coefficient. Others explain public health research design, including community studies, and address the value and limitations of case reports and case series. Of particular note is a decision chart to help in choosing appropriate research designs. Health students and faculty will desire an online version of this gem!" —CHOICE Issues of health and disease are central to human life, so an understanding of the science of epidemiology—the study of the patterns of disease and injury in human populations—is relevant to everyone. Many areas of study are directly concerned with epidemiological issues, including medicine and nursing, public policy, health administration, and the social and behavioral sciences. The Encyclopedia of Epidemiology presents state-of-the-art information from the field of epidemiology in a less technical and accessible style and format. With more than 600 entries, no single reference provides as comprehensive a resource in as focused and appropriate manner. The entries cover every major facet of epidemiology, from risk ratios to case-control studies to mediating and moderating variables, and much more. Relevant topics from related fields such as biostatistics and health economics are also included. Key Features Presents a Reader′s Guide to organize entries around themes or specific topics and easily guide users to areas of interest Offers cross-referenced terms, a brief listing of Further Readings, and stable Web site URLs following most entries Provides appendices that include a general bibliography to build on Further Readings, an annotated list of organizations relevant to epidemiology, the standard statistical tables used in epidemiology (t-distribution, F-table, normal [z] distribution, chi-square, etc.), and flow charts to aid researchers in selecting an appropriate study design This resource is a must-have for students, practitioners, researchers, and the informed public who want to know more about health and disease and related topics.

This book describes various ways of approaching and interpreting the data produced by clinical trial studies, with a special emphasis on the essential role that biostatistics plays in clinical trials. Over the past few decades the role of statistics in the evaluation and interpretation of clinical data has become of paramount importance. As a result the standards of clinical study design, conduct and interpretation have undergone substantial improvement. The book includes 18 carefully reviewed chapters on recent developments in clinical trials and their statistical evaluation, with each chapter providing one or more examples involving typical data sets, enabling readers to apply the proposed procedures. The chapters employ a uniform style to enhance comparability between the approaches.

Presents elements of clinical trial methods that are essential in planning, designing, conducting, analyzing, and interpreting clinical trials with the goal of improving the evidence derived from these important studies This Third Edition builds on the text’s reputation as a straightforward, detailed, and authoritative presentation of quantitative methods for clinical trials. Readers will encounter the principles of design for various types of clinical trials, and are then skillfully guided through the complete process of planning the experiment, assembling a study cohort, assessing data, and reporting results. Throughout the process, the author alerts readers to problems that may arise during the course of the trial and provides common sense solutions. All stages of therapeutic development are discussed in detail, and the methods are not restricted to a single clinical application area. The authors bases current revisions and updates on his own experience, classroom instruction, and feedback from teachers and medical and statistical professionals involved in clinical trials. The Third Edition greatly expands its coverage, ranging from statistical principles to new and provocative topics, including alternative medicine and ethics, middle development, comparative studies, and adaptive designs. At the same time, it offers more pragmatic advice for issues such as selecting outcomes, sample size, analysis, reporting, and handling allegations of misconduct. Readers familiar with the First and Second Editions will discover revamped exercise sets; an updated and extensive reference section; new material on endpoints and the developmental pipeline, among others; and revisions of numerous sections. In addition, this book: • Features accessible and broad coverage of statistical design methods—the crucial building blocks of clinical trials and medical research -- now complete with new chapters on overall development, middle development, comparative studies, and adaptive designs • Teaches readers to design clinical trials that produce valid qualitative results backed by rigorous statistical methods • Contains an introduction and summary in each chapter to reinforce key points • Includes discussion questions to stimulate critical thinking and help readers understand how they can apply their newfound knowledge • Provides extensive references to direct readers to the most recent literature, and there are numerous new or revised exercises throughout the book Clinical Trials: A Methodologic Perspective, Third Edition is a textbook accessible to advanced undergraduate students in the quantitative sciences, graduate students in public health and the life sciences, physicians training in clinical research methods, and biostatisticians and epidemiologists. This book is accompanied by downloadable files available below under the DOWNLOADS tab. These files include: MATHEMATICA program – A set of downloadable files that tracks the chapters, containing code pertaining to each. SAS PROGRAMS and DATA FILES used in the book. The following software programs, included in the downloadables, were developed by the author, Steven Piantadosi, M.D., Ph.D: RANDOMIZATION – This program generates treatment assignments for a clinical trial using blocked stratified randomization. CRM – Implements the continual reassessment methods for dose finding clinical trials. OPTIMAL – Calculates two-stage optimal phase II designs using the Simon method. POWER – This is a power and sample size program for clinical trials. Executables for installing these programs can also be found at https://risccweb.csmc.edu/biostats/. Steven Piantadosi, MD, PhD, is the Phase One Foundation Distinguished Chair and Director of the Samuel Oschin Cancer Institute, and Professor of Medicine at Cedars-Sinai Medical Center in Los Angeles, California. Dr. Piantadosi is one of the world’s leading experts in the design and analysis of clinical trials for cancer research. He has taught clinical trials methods extensively in formal courses and short venues. He has advised numerous academic programs and collaborations nationally regarding clinical trial design and conduct, and has served on external advisory boards for the National Institutes of Health and other prominent cancer programs and centers. The author of more than 260 peer-reviewed scientific articles, Dr. Piantadosi has published extensively on research results, clinical applications, and trial methodology. While his papers have contributed to many areas of oncology, he has also collaborated on diverse studies outside oncology including lung disease and degenerative neurological disease.

The Reviewer’s Guide to Quantitative Methods in the Social Sciences provides evaluators of research manuscripts and proposals in the social and behavioral sciences with the resources they need to read, understand, and assess quantitative work. 35 uniquely structured chapters cover both traditional and emerging methods of quantitative data analysis, which neither junior nor veteran reviewers can be expected to know in detail. The second edition of this valuable resource updates readers on each technique’s key principles, appropriate usage, underlying assumptions and limitations, providing reviewers with the information they need to offer constructive commentary on works they evaluate. Written by methodological and applied scholars, this volume is also an indispensable author’s reference for preparing sound research manuscripts and proposals.