Statistics for Health Care Professionals: An Introduction
Ian Scott and Deborah Mazhindu

Sage 2005 ISBN: 0761974768, 076197475X 248 pages PDF 1,4 MB

A companion website is available for this !
Statistics for Health Care Professionals is an accessible guide to understanding statistics within health care practice. Focusing on quantitative approaches to investigating problems, the book introduces the basic rules and principles of statistics.

Challenging the notion that statistics are often incomprehensible and complex to use, the authors begin presenting a `how to’ section explaining how specific statistical tests can be performed. They also help readers to understand the language of statistics, which is often a stumbling block for those coming to the subject for the first time. The reader is taught how to calculate statistics hand as well as being introduced to computer packages to make life easier, and then how to analyse these results.

As the results of health care research are so integral to decision-making and developing new practice within the profession, the book encourages the reader to think critically about data analysis and research design, and how these can impact upon evidence based practice. This critical stance is also crucial in the assessment of the many reports and documents issued within the health industry.

Statistics for Health Care Professionals includes practical examples of statistical techniques throughout, and the exercises within and at the end of each chapter help readers to learn and to develop proficiency. There is also a glossary at the end of the book for quick and easy referencing.

This book is essential reading for those coming to statistics for the first time within a health care setting.

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Modern Multivariate Statistical Techniques: Regression, Classification, and Manifold Learning
Alan Julian Izenman

Springer 2008-08-28 ISBN: 0387781889 734 pages PDF 10,7 MB

Remarkable advances in computation and data storage and the ready availability of huge data sets have been the keys to the growth of the new disciplines of data mining and machine learning, while the enormous success of the Human Genome Project has opened up the field of bioinformatics.

These exciting developments, which led to the introduction of many innovative statistical tools for high-dimensional data analysis, are described here in detail. The author takes a broad perspective; for the first time in a book on multivariate analysis, nonlinear methods are discussed in detail as well as linear methods. Techniques covered range from traditional multivariate methods, such as multiple regression, principal components, canonical variates, linear discriminant analysis, factor analysis, clustering, multidimensional scaling, and correspondence analysis, to the newer methods of density estimation, projection pursuit, neural networks, multivariate reduced-rank regression, nonlinear manifold learning, bagging, boosting, random forests, independent component analysis, support vector machines, and classification and regression trees. Another unique feature of this book is the discussion of database management systems.

This book is appropriate for advanced undergraduate students, graduate students, and researchers in statistics, computer science, artificial intelligence, psychology, cognitive sciences, business, medicine, bioinformatics, and engineering. Familiarity with multivariable calculus, linear algebra, and probability and statistics is required. The book presents a carey-integd mixture of theory and applications, and of classical and modern multivariate statistical techniques, including Bayesian methods. There are over 60 interesting data sets used as examples in the book, over 200 exercises, and many color illustrations and photographs.

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Analyzing the Large Number of Variables in Biomedical and Satellite Imagery
Phillip I. Good

Publisher: Wiley 2011 187 Pages ISBN: 0470927143 PDF 4 MB

This book grew out of an online interactive offered through statcourse.com, and it soon became apparent to the author that the course was too limited in terms of time and length in light of the broad backgrounds of the enrolled students. The statisticians who took the course needed to be brought up to speed both on the biological con as well as on the specialized statistical methods needed to handle large arrays. Biologists and physicians, even though y knowledgeable concerning the procedures used to gene microaarrays, EEGs, or MRIs, needed a introduction to the resampling methods—the bootstrap, decision trees, and permutation tests, before the specialized methods applicable to large arrays could be introduced. As the intended audience for this book consists both of statisticians and of medical and biological research workers as well as all those research workers who make use of satellite imagery including agronomists and meteorologists, the book provides a step–step approach to not only the specialized methods needed to analyze the data from microarrays and images, but also to the resampling methods, step-down multi-comparison procedures, multivariate analysis, as well as data collection and pre-processing. While many alternate techniques for analysis have been introduced in the past decade, the author has selected only those techniques for which software is available along with a list of the available links from which the software may be purchased or downloaded without charge. Topical coverage includes: very large arrays; permutation tests; applying permutation tests; gathering and preparing data for analysis; multiple tests; bootstrap; applying the bootstrap; classification methods; decision trees; and applying decision trees.

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Essential Epidemiology: An Introduction for Students and Health Professionals – 2nd Edition
Penny Webb, Chris Bain

• Pub. Date: January 2011
• Publisher: Cambridge University Press
• ISBN-13: 9780521177313
• ISBN: 0521177316

Synopsis

The new edition of this popular book remains a clear and practical introduction to epidemiology for students in all areas of health. emphasising the role of epidemiology across a broad range of health monitoring and research, it gives students an understanding of the fundamental principles common to all areas of epidemiology. It also integs the study of infectious and chronic as well as public health and clinical epidemiology. Avoiding complex mathematics, it steps through the methods and potential problems underlying health data and reports, while maintaining a balance of rigour and clarity. The nuts-and-bolts of epidemiology are embedded in the wider international health perspective through recent and classical examples across different areas of health to engage students from a range of backgrounds. Concepts are illustd with charts and graphs, and end-of-chapter questions test understanding (with answers provided). Online resources include further exercises, slides for teaching and useful weblinks.

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Sample Size Tables for Clinical Studies- 3rd Edition

David Machin, Michael J. Campbell, Sze-huey Tan, Say-Beng Tan, Sze-Huey Tan

• Publisher: John Wiley and Sons; 3 edition (December 16, 2008)
• Language: English
• ISBN-10: 1405146508
• ISBN-13: 978-1405146500

his book provides statisticians and researchers with the statistical tools – equations, formula and numerical tables – to design and plan clinical studies and carry out accu, reliable and reproducible analysis of the data so obtained. There is no way around this as incorrect procedure in clinical studies means that the researcher’s paper will not be accepted a peer-reviewed journal. Planning and analyzing clinical studies is a very complicated business and this book provides indispensable factual information.

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Epidemiological Research: Terms and Concepts
O. S. Miettinen

Springer 2011 ISBN: 9400711700 191 pages PDF 1,5 MB

This book is a single author – someone who, after medical school, has devoted half-a-century of -time effort to ever better understand both clinical and community medicine and the research that is needed to produce the scientific knowledge-base of these.

The book is organized so as to address in sepa sections first the preparatory topics of medicine (clinical and epidemiological), science in general, and statistics (mathematical); then topics of epidemiological research proper; and, finally, topics of ‘meta-epidemiological’ clinical research. In those two main sections, a further grouping is based on the distraction between objects and methods of study. In this framework, the particular topics are addressed both descriptively and quasi-prescriptively, commonly with a number of explicatory annotations.

This book is intended to serve and a handbook for whomever is, in whatever way, concerned with epidemiological or ‘meta-epidemiological’ clinical research. But besides, it is intended to serve as a book for the students in introductory courses on ‘epidemiological’ research – to which end there is a suggested hierarchy of the concepts that might reasonably be covered.

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