Biostatistics

Biostatistics with R An Introductory Guide for Field Biologists

Jan Lepš

University of South Bohemia, Czech Republic

and Petr Šmilauer

University of South Bohemia, Czech Republic A straightforward introduction on how to analyse data from the field of biological research and conservation. All chapters are supplemented by thoroughly explained R code demonstrating interpretation of the results. An ideal reference for students, researchers and professionals, as well as lecturers of undergraduate courses. 2020 247 x 174 mm c.384pp 978-1-108-48038-3 Hardback £69.99 / US$89.99 978-1-108-72734-1 Paperback £26.99 / US$34.99

Publication July 2020

For all formats available, see www.cambridge.org/9781108480383 Applied Mixed Model Analysis A Practical Guide Second edition

Jos W. R. Twisk

Universiteit van Amsterdam This book explains all aspects of mixed model analysis without mathematical jargon, so that non-statisticians can understand the basic principles, analyze their own data, and interpret the results with confidence. Worked examples are analyzed with STATA, and all datasets are available for download, equipping readers to replicate the methods.

Practical Guides to Biostatistics and Epidemiology

2019 247 x 174 mm 246pp 978-1-108-48057-4 Hardback £99.99 / US$130.00 978-1-108-72776-1 Paperback £44.99 / US$59.99 For all formats available, see www.cambridge.org/9781108480574

A Course in Morphometrics for Biologists Geometry and Statistics for Studies of Organismal Form

Fred L. Bookstein

University of Washington This book teaches not only the ‘how’ for statistical analysis of organismal size and shape, but also the ‘when’ and the ‘why’. Aimed at graduate students and researchers, it covers the whole range of today’s best techniques while always emphasizing the ways that arithmetic leads to biological understanding.

‘This is a pioneering and outstanding book with its interdisciplinary style of presentation, which aids the reader’s understanding of morphometrics (shape analysis) and explains how to apply its tools. It does not hesitate to use a wide variety of subjects to achieve its objectives: statistics, algebra and arithmetic. To make it a hands-on text, it also provides S+ code of the tools described. The text is very user-friendly as it is written in an informal and accessible style. The book will be essential reading for researchers and students in the area; it demonstrates exquisite scholarship and I cannot recommend this text more highly.’

K. V. Mardia, University of Leeds

‘This is a unique book; one that not only provides the basic formulae and concepts for undertaking quantitative data analyses, but also explains and illustrates the origins of these concepts, the controversies they embody, their links to other branches of science, and the personalities behind their creation. It’s a marvellous tour de force and one I suspect few others could have written with such verve and authority. Required reading for anyone seeking to understand – and especially to teach – methods of linear data analysis generally and the analysis of morphological data in particular.’

Norman MacLeod, The Natural History Museum, London

2018 228 x 152 mm 544pp 978-1-107-19094-8 Hardback £64.99 / US$89.99 For all formats available, see www.cambridge.org/9781107190948

Experimental Design for Laboratory Biologists Maximising Information and Improving Reproducibility

Stanley E. Lazic

AstraZeneca An ideal resource for anyone conducting lab-based biomedical research, this guide shows how to design reproducible experiments that have low bias, high precision and widely applicable results. It explores key ideas in experimental design, including reproducibility and replication, assesses common designs, and shows how to plan for success.

‘This is a wonderfully lucid introduction to experimental design, written by an author who is clearly aware of the pitfalls that exist for the unwary experimenter. The focus is on how to design experiments to ensure reproducible research, with many examples illustrating general principles that need to be understood to avoid error and bias. The coverage of statistical analysis follows on naturally from the design issues, and is amply illustrated with exercises in R. Highly recommended.’

Dorothy Bishop, University of Oxford

‘Worldwide there is a salient discussion about deficiencies in the validity and predictiveness of research in the life sciences. Indeed, a fullblown ‘reproducibility crisis’ has been proclaimed. Against this backdrop this important textbook is a timely and highly useful contribution in the pressing quest to improve the robustness, rigor, and reproducibility of current biological and preclinical research. Proper experimental design is the bedrock for obtaining reliable evidence. By providing the necessary conceptual know-how and practical knowledge, [this book] enables investigators in all stages of their careers to minimize bias and improve statistical power through proper design and analysis of their experiments. This volume is unique … [as] it is immensely readable and accessible even for those with little previous knowledge, in combining all relevant aspects in a practical, concise and comprehensive manner, and in its clear focus on factors that help to improve the quality of research.’

Ulrich Dirnagl, Charité University Hospital, Germany

2016 246 x 189 mm 422pp 124 b/w illus. 978-1-107-42488-3 Paperback £39.99 / US$51.99 For all formats available, see www.cambridge.org/9781107424883