Introduction to Statistical Analysis of LaboratoryData - Hardcover

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Alfred A. Bartolucci is Professor Emeritus in the Department of Biostatistics, School of Public Health, University of Alabama at Birmingham. He has over 300 peer-reviewed publications (manuscripts and book chapters) in the areas of original statistical methodologic research and clinical and laboratory statistical applications. An endowed scholarship in Biostatistics at UAB was established in his honor.

Karan P. Singh is currently Professor of Medicine and serves as Director of the Biostatistics and Bioinformatics Shared Facility at the University of Alabama at Birmingham Comprehensive Cancer Center. He has authored or coauthored over 250 peer-reviewed articles, book chapters, and peer-reviewed congress or conference proceedings. He is a Fellow of the American Statistical association.

Sejong Bae is Professor of Medicine and serves as Co-Director of the Biostatistics and Bioinformatics Shared Facility; Deputy Director of the Coronary Artery Risk Development in Young Adults Coordination Center; and Director of Data, Information, and Statistics Core in the Division of Preventive Medicine. In 2009, he was elected to International Statistical Institute.

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There is an unmet need to have the necessary statistical tools in a comprehensive package with a focus on laboratory experimentation. The study of the statistical handling of laboratory data from the design, analysis, and graphical perspective is essential for understanding pharmaceutical research and development of results involving practical quantitative interpretation and communication of the experimental process.

Introduction to Statistical Analysis of Laboratory Data presents a detailed discussion of important basic statistical concepts and methods of data presentation and analysis in aspects of biological experimentation requiring a fundamental knowledge of probability and the foundations of statistical inference, including basic statistical terminology such as simple geometric statistics and transformations needed to effectively communicate and understand one's data results.

Advanced topics of the book go beyond the basics and cover more complex issues in laboratory investigations with examples, including association studies such as correlation and regression analysis with laboratory applications such as dose–response and nonlinear dose–response considerations. Where relevant, the procedures provided follow the CLSI (Clinical and Laboratory Standards Institute) guidelines for data handling and presentation.

Introduction to Statistical Analysis of Laboratory Data presents the following data:

• A comprehensive package of statistical tools (simple, cross sectional, longitudinal) required in laboratory experimentation
• A solid introduction to the terminology used in many applications such as the interpretation of assay design and validation as well as "fit-for-purpose" procedures
• A rigorous review of statistical quality control procedures in laboratory methodologies and influences on capabilities
• A thorough presentation of methodologies used in the areas such as method comparison procedures, limit and bias detection, outlier analysis, and detecting sources of variation

Introduction to Statistical Analysis of Laboratory Data is suitable for graduate students in biology, chemistry, physical pharmacy, pharmaceutics, environmental health sciences and engineering, and biopharmaceutics.