Human health risk assessment involves the measuring of risk of exposure to disease, with a view to improving disease prevention. Mathematical, biological, statistical, and computational methods play a key role in exposure assessment, hazard assessment and identification, and dose-response modelling.

Recent Advances in Quantitative Methods in Cancer and Human Health Risk Assessment is a comprehensive text that accounts for the wealth of new biological data as well as new biological, toxicological, and medical approaches adopted in risk assessment. It provides an authoritative...

Mathematical models are used to simulate complex real-world phenomena in many areas of science and technology. Large complex models typically require inputs whose values are not known with certainty. Uncertainty analysis aims to quantify the overall uncertainty within a model, in order to support problem owners in model-based decision-making. In recent years there has been an explosion of interest in uncertainty analysis. Uncertainty and dependence elicitation, dependence modelling, model inference, efficient sampling, screening and sensitivity analysis, and probabilistic inversion are among...

A respected introduction to biostatistics, thoroughly updated and revised

The first edition of Biostatistics: A Methodology for the Health Sciences has served professionals and students alike as a leading resource for learning how to apply statistical methods to the biomedical sciences. This substantially revised Second Edition brings the book into the twenty-first century for today's aspiring and practicing medical scientist.

This versatile reference provides a wide-ranging look at basic and advanced biostatistical concepts and methods in a format calibrated to individual interests and...

This book contains material on compound Poisson random variables including an identity which can be used to efficiently compute moments, Poisson approximations, and coverage of the mean time spent in transient states as well as examples relating to the Gibba s sampler, the Metropolis algorithm and mean cover time in star graphs.

How to apply statistical methods to survey data--a guide to effective analysis of health surveys.

With large health surveys becoming increasingly available for public use, researchers with little experience in survey methods are often faced with analyzing data from surveys to address scientific and programmatic questions. This practical book provides statistical techniques for use in survey analysis, making health surveys accessible to statisticians, biostatisticians, epidemiologists, and health researchers. The authors clearly explain the theory and methods of survey analysis...

A comprehensive account of economic size distributions around the world and throughout the years

In the course of the past 100 years, economists and applied statisticians have developed a remarkably diverse variety of income distribution models, yet no single resource convincingly accounts for all of these models, analyzing their strengths and weaknesses, similarities and differences. Statistical Size Distributions in Economics and Actuarial Sciences is the first collection to systematically investigate a wide variety of parametric models that deal with income, wealth, and related...

The brand new edition of this classic text--with more exercises and easier to use than ever Like the first edition, this new version of Lamperti's classic text succeeds in making this fascinating area of mathematics accessible to readers who have limited knowledge of measure theory and only some familiarity with elementary probability. Streamlined for even greater clarity and with more exercises to help develop and reinforce skills, Probability is ideal for graduate and advanced undergraduate students--both in and out of the classroom. Probability covers:
* Probability spaces, random...

Regression analysis is a commonly used statistical tool in constructing mathematical models from experimental data.

The latest computer assisted methods for survey research

Computer assisted survey information collection (CASIC) methods are rapidly replacing traditional "paper and pencil" survey procedures. Researchers now apply computer technologies at every step of the survey process, from automating interviews and computerizing data collection to data capture and preparation. CASIC techniques are reshaping today's survey research and methodology --and redefining tomorrow's.

Computer Assisted Survey Information Collection is the most up-to-date and authoritative resource...

This volume makes up one of two books in a series on continuous multivariate distributions (CMD). Johnson and Kotz published the original, single volume in 1972. The subject has developed greatly since that time, with possible applications such as understanding the complexities of flood, quake, rainfall, and wind control, and now constitutes two broadly classified areas: sampling and modelling.