Statistical Theory and Analysis in Bioassay is a seven chapter monograph tailored essentially to meet the needs of graduate students, practitioners and researchers in the fields of medicine, pharmacology, biosciences/life sciences and related fields that employs the tools of biostatistics in bioassays and analysis. In this wise, we have taken time to discuss in details relevant topics; principles, methods and applications. Practice exercises are also included where necessary. The earlier chapters give background information, definition of terms, purpose, types, structure and relative potency in bioassay. An important theorem, Fieller’s theorem is proved in details with illustrative examples. The last two chapters are on dose-response relationship, fitting in parallelline assays and estimation. We are convinced that this monograph will meet the expectations of the readers while constructive criticisms that will improve another edition will be appreciated.

The Statistics of Bioassay: With Special Reference to the Vitamins, Volume II focuses on the processes, reactions, principles, and approaches involved in the biological assay of vitamins. The publication first offers information on the general principles of biological assay, dosage-response curve and its error, and designs for segregating nonrandom variation. Discussions focus on replacement of missing values, randomized groups, calculation of the line, analysis of the variation about the line, comparative biological assays, analytical biological assays, and determination of activity. The text then ponders on measurement of relative potency and correction of quantitative variables. The manuscript takes a look at assays where the variation in response is a function of the dose and slope-ratio assays. Topics include microbiological assays and the slope-ratio technique, analysis of balanced slope-ratio assays, analysis of assays with an all-or-none response, and graded response with unequal variance. The publication then tackles multiple or repeated assays, including quality control in repeated assays and combination of independent assays of a single unknown. The publication is a valuable source of information for researchers interested in the biological assay of vitamins.

This volume provides background theory and practical protocols for bioassays of bacteria, viruses, fungi and nematodes that can be used as biological control agents against insect pests of agricultural and medical importance.

This textbook teaches crucial statistical methods to answer research questions using a unique range of statistical software programs, including MINITAB and R. This textbook is developed for undergraduate students in agriculture, nursing, biology and biomedical research. Graduate students will also find it to be a useful way to refresh their statistics skills and to reference software options. The unique combination of examples is approached using MINITAB and R for their individual strengths. Subjects covered include among others data description, probability distributions, experimental design, regression analysis, randomized design and biological assay. Unlike other biostatistics textbooks, this text also includes outliers, influential observations in regression and an introduction to survival analysis. Material is taken from the author's extensive teaching and research in Africa, USA and the UK. Sample problems, references and electronic supplementary material accompany each chapter.

Now in its third edition, this classic book is widely considered the leading text on Bayesian methods, lauded for its accessible, practical approach to analyzing data and solving research problems. Bayesian Data Analysis, Third Edition continues to take an applied approach to analysis using up-to-date Bayesian methods. The authors—all leaders in the statistics community—introduce basic concepts from a data-analytic perspective before presenting advanced methods. Throughout the text, numerous worked examples drawn from real applications and research emphasize the use of Bayesian inference in practice. New to the Third Edition Four new chapters on nonparametric modeling Coverage of weakly informative priors and boundary-avoiding priors Updated discussion of cross-validation and predictive information criteria Improved convergence monitoring and effective sample size calculations for iterative simulation Presentations of Hamiltonian Monte Carlo, variational Bayes, and expectation propagation New and revised software code The book can be used in three different ways. For undergraduate students, it introduces Bayesian inference starting from first principles. For graduate students, the text presents effective current approaches to Bayesian modeling and computation in statistics and related fields. For researchers, it provides an assortment of Bayesian methods in applied statistics. Additional materials, including data sets used in the examples, solutions to selected exercises, and software instructions, are available on the book’s web page.

The goal of an activity-directed isolation process is to isolate bioactive compounds which may provide structural leads of therapeutic importance. Whereas the traditional process of drug development is long and expensive, simple and rapid bioassays can serve as the starting point for drug discovery. This book presents a range of "bench top" bioassa

In recent decades, there has been enormous growth in biologics research and development, with the accompanying development of biological assays for emerging products. In parallel, there have been substantial advances in statistical methodology, as well as technological advances in computer power, enabling new techniques to be implemented via statistical software. Biostatistics for Bioassay presents an overview of the statistical analysis techniques that are needed in order to report the results of biological assays. These assays are needed for testing all biological medicines, such as vaccines and cell therapies, to allow them to be released for use. Beginning with consideration of the performance characteristics required of a bioassay, including accuracy, precision, and combinations of these two attributes, the book builds a framework for statistical bioassay design. Features: Explains the statistical methods needed at each stage of the lifecycle of a bioassay Describes the demonstration of the bioassay’s performance, known as validation Covers the statistical techniques for monitoring the bioassay’s performance over time Details how to transfer the bioassay to another laboratory or replace critical reagents Provides examples at every stage, to allow the reader to work through the techniques and consolidate their understanding The book provides a resource for interested bioassay analysts, and statisticians working with bioassays. In bringing together best practices in statistics across the bioassay lifecycle into a single volume, it aims to provide a comprehensive and useful textbook for statistical analysis in bioassay.

The apparent contradiction between statistical significance and biological relevance has diminished the value of statistical methods as a whole in toxicology. Moreover, recommendations for statistical analysis are imprecise in most toxicological guidelines. Addressing these dilemmas, Statistics in Toxicology Using R explains the statistical analysi

This rewritten and updated second edition provides comprehensive information on the wide-ranging applications of statistics in the pharmacological field. Focusing on practical aspects, it sets out to bridge the gap between industry and academia.;Reflecting the changes that have taken place since publication of the first edition, this volume covers new topics such as: cancer clinical trials, clinical trials of AIDS patients and animal tumorigenicity studies; the development of antiepileptic drugs; the role of epidemiology in postmarketing trials and adverse drug experience; computer-assisted new drug application (CANDA) submissions; contract research organizations; interim analysis in clinical trials; and room-temperature tests for the stability of drugs.;This work is intended as: a reference for statisticians, biostatisticians, pharmacologists, administrators, managers, and scientists in the pharmaceutical industry; and a text for graduate students taking courses in applied statistics or pharmaceutical statistics.