Now viewed as its own scientific discipline, clinical trial methodology encompasses the methods required for the protection of participants in a clinical trial and the methods necessary to provide a valid inference about the objective of the trial. Drawing from the authors' courses on the subject as well as the first author's more than 30 years working in the pharmaceutical industry, Clinical Trial Methodology emphasizes the importance of statistical thinking in clinical research and presents the methodology as a key component of clinical research.
From...
Now viewed as its own scientific discipline, clinical trial methodology encompasses the methods required for the protection of participants in a cl...
The concept of frailty offers a convenient way to introduce unobserved heterogeneity and associations into models for survival data. In its simplest form, frailty is an unobserved random proportionality factor that modifies the hazard function of an individual or a group of related individuals. Frailty Models in Survival Analysis presents a comprehensive overview of the fundamental approaches in the area of frailty models.
The book extensively explores how univariate frailty models can represent unobserved heterogeneity. It also emphasizes correlated frailty...
The concept of frailty offers a convenient way to introduce unobserved heterogeneity and associations into models for survival data. In its simples...
Helping you become a creative, logical thinker and skillful "simulator," Monte Carlo Simulation for the Pharmaceutical Industry: Concepts, Algorithms, and Case Studies provides broad coverage of the entire drug development process, from drug discovery to preclinical and clinical trial aspects to commercialization. It presents the theories and methods needed to carry out computer simulations efficiently, covers both descriptive and pseudocode algorithms that provide the basis for implementation of the simulation methods, and illustrates real-world problems through case studies.
The text...
Helping you become a creative, logical thinker and skillful "simulator," Monte Carlo Simulation for the Pharmaceutical Industry: Concepts, Algorith...
Optimal Design for Nonlinear Response Models discusses the theory and applications of model-based experimental design with a strong emphasis on biopharmaceutical studies. The book draws on the authors many years of experience in academia and the pharmaceutical industry.
While the focus is on nonlinear models, the book begins with an explanation of the key ideas, using linear models as examples. Applying the linearization in the parameter space, it then covers nonlinear models and locally optimal designs as well as minimax, optimal on average, and Bayesian...
Optimal Design for Nonlinear Response Models discusses the theory and applications of model-based experimental design with a stron...
Statistical Testing Strategies in the Health Sciences provides a compendium of statistical approaches for decision making, ranging from graphical methods and classical procedures through computationally intensive bootstrap strategies to advanced empirical likelihood techniques. It bridges the gap between theoretical statistical methods and practical procedures applied to the planning and analysis of health-related experiments.
The book is organized primarily based on the type of questions to be answered by inference procedures or according to the general...
Statistical Testing Strategies in the Health Sciences provides a compendium of statistical approaches for decision making, ranging...
Helping you become a creative, logical thinker and skillful "simulator," Monte Carlo Simulation for the Pharmaceutical Industry: Concepts, Algorithms, and Case Studies provides broad coverage of the entire drug development process, from drug discovery to preclinical and clinical trial aspects to commercialization. It presents the theories and methods needed to carry out computer simulations efficiently, covers both descriptive and pseudocode algorithms that provide the basis for implementation of the simulation methods, and illustrates real-world problems through case studies.
The text first...
Helping you become a creative, logical thinker and skillful "simulator," Monte Carlo Simulation for the Pharmaceutical Industry: Concepts, Algorithms,...
Using time-to-event analysis methodology requires careful definition of the event, censored observation, provision of adequate follow-up, number of events, and independence or "noninformativeness" of the censoring mechanisms relative to the event. Design and Analysis of Clinical Trials with Time-to-Event Endpoints provides a thorough presentation of the design, monitoring, analysis, and interpretation of clinical trials in which time-to-event is of critical interest.
After reviewing time-to-event endpoint methodology, clinical trial issues, and the design and monitoring of clinical trials,...
Using time-to-event analysis methodology requires careful definition of the event, censored observation, provision of adequate follow-up, number of ev...
Theory of Drug Development presents a formal quantitative framework for understanding drug development that goes beyond simply describing the properties of the statistics in individual studies. It examines the drug development process from the perspectives of drug companies and regulatory agencies.
By quantifying various ideas underlying drug development, the book shows how to systematically address problems, such as:
Sizing a phase 2 trial and choosing the range of p-values that will trigger a follow-up phase 3 trial Deciding whether a drug should receive marketing approval based on its...
Theory of Drug Development presents a formal quantitative framework for understanding drug development that goes beyond simply describing the properti...
Showcasing a discussion of the experimental process and a review of basic statistics, this volume provides methodologies to identify general data distribution, skewness, and outliers. It features a unique classification of the nonparametric analogs of their parametric counterparts according to the strength of the collected data. Applied Statistical Designs for the Researcher discusses three varieties of the Student t test, including a comparison of two different groups with different variances; two groups with the same variance; and a matched, paired group. It introduces the analysis of...
Showcasing a discussion of the experimental process and a review of basic statistics, this volume provides methodologies to identify general data dist...
This remarkable text raises the analysis of data in health sciences and policy to new heights of refinement and applicability by introducing cutting-edge meta-analysis strategies while reviewing more commonly used techniques. Each chapter builds on sound principles, develops methodologies to solve statistical problems, and presents concrete applications used by experienced medical practitioners and health policymakers. Written by more than 30 celebrated international experts, Meta-Analysis in Medicine and Health Policy employs copious examples and pictorial presentations to teach and...
This remarkable text raises the analysis of data in health sciences and policy to new heights of refinement and applicability by introducing cutting-e...
