Statistical Methods And Safety Data Analysis And Evaluation

Medical Product Safety Evaluation: Biological Models and Statistical Methods presents cutting-edge biological models and statistical methods that are tailored to specific objectives and data types for safety analysis and benefit-risk assessment. Some frequently encountered issues and challenges in the design and analysis of safety studies are discussed with illustrative applications and examples. Medical Product Safety Evaluation: Biological Models and Statistical Methods presents cutting-edge biological models and statistical methods that are tailored to specific objectives and data types for safety analysis and benefit-risk assessment. Some frequently encountered issues and challenges in the design and analysis of safety studies are discussed with illustrative applications and examples. The book is designed not only for biopharmaceutical professionals, such as statisticians, safety specialists, pharmacovigilance experts, and pharmacoepidemiologists, who can use the book as self-learning materials or in short courses or training programs, but also for graduate students in statistics and biomedical data science for a one-semester course. Each chapter provides supplements and problems as more readings and exercises.

Covers empirical approaches to outlier detection in intelligent transportation systems data, modeling of traffic crash-flow relationships for intersections, profiling of high-frequency accident locations by use of association rules, analysis of rollovers and injuries with sport utility vehicles, and automated accident detection at intersections via digital audio signal processing.

"Includes 30 papers that explore modeling crash frequency by severity, time series analysis of road risk, crash data analysis using bootstrapped maximum likelihood method, time series analysis of the effect of holidays on daily traffic counts, regression-to-mean effect in traffic safety evaluation, roundabouts, and the safety impact of improved signal visibility."--TRB summary website.

This Transportation Research Record contains 28 papers dealing with statistical methods in highway safety research; highway safety data, analysis, and evaluation; occupant protection; and systematic reviews and meta-analysis. The papers address such topics as risk and crash prediction models, crashes on freeways and at signalized intersections, multivehicle crash prediction, speed and safety, red light running crashes, freeway lane closures, ramp design, accident exposure, rumble strip benefits, collisions with median trees, intersection safety, accident reconstruction, safety effects of speed limit changes, geometric design and head-on crashes, deer-vehicle crashes, sport utility vehicle rollover, vehicle occupancy and crash risk, a logit model for studying injury severity, abdominal injuries in rail passengers, healthy transport policies, and meta-analysis.

State-of-the-Art Methods for Drug Safety Assessment Responding to the increased scrutiny of drug safety in recent years, Quantitative Evaluation of Safety in Drug Development: Design, Analysis and Reporting explains design, monitoring, analysis, and reporting issues for both clinical trials and observational studies in biopharmaceutical product development. It presents the latest statistical methods for drug safety assessment. The book’s three sections focus on study design, safety monitoring, and data evaluation/analysis. The book addresses key challenges across regulatory agencies, industry, and academia. It discusses quantitative approaches to safety evaluation and risk management in drug development, covering Bayesian methods, effective safety graphics, and risk-benefit evaluation. Written by a team of experienced leaders, this book brings the most advanced knowledge and statistical methods of drug safety to the statistical, clinical, and safety community. It shares best practices and stimulates further research and methodology development in the drug safety area.

This book provides a comprehensive introduction to methods and models for categorical data analysis and their applications in social science research. Companion website also available, at https://webspace.utexas.edu/dpowers/www/