Biostatistics For Bioassay
Download Biostatistics For Bioassay PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Biostatistics For Bioassay book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages.
Biostatistics for Bioassay
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.
Statistical Techniques in Bioassay
Author: Z. Govindarajulu
language: en
Publisher: Karger Medical and Scientific Publishers
Release Date: 2001-01-03
In the face of the ever-increasing importance of statistical methods in medical research and practice, the first edition of this publication has provided a sound and deep understanding of statistical methods in bioassay to many students and researchers. In addition to the profound presentation of statistical methods of the first edition, here the reader will find new material stemming from the recent statistical literature as well as data reflecting modern trends in general applied statistical research. Examples are discussions on design and planning, e.g. choices of dose levels, an additional section in the chapter on Bayes methods, and a new chapter on sequential estimation for the logistic model. The book will be a valuable source of information to students in the experimental area of statistical aspects of biological assay, professional statisticians with an interest in research in this topic, teachers in statistics and biology, and investigators in the biological and medical sciences who use bioassay in their work.
Introduction to Statistical Analysis of Laboratory Data
Author: Alfred Bartolucci
language: en
Publisher: John Wiley & Sons
Release Date: 2015-11-02
Introduction to Statistical Analysis of Laboratory Data presents a detailed discussion of important statistical concepts and methods of data presentation and analysis Provides detailed discussions on statistical applications including a comprehensive package of statistical tools that are specific to the laboratory experiment process Introduces terminology used in many applications such as the interpretation of assay design and validation as well as “fit for purpose” procedures including real world examples Includes a rigorous review of statistical quality control procedures in laboratory methodologies and influences on capabilities Presents methodologies used in the areas such as method comparison procedures, limit and bias detection, outlier analysis and detecting sources of variation Analysis of robustness and ruggedness including multivariate influences on response are introduced to account for controllable/uncontrollable laboratory conditions