Brian S. Everitt

Handbook of Statistical Analyses Using R, Second Edition

Sabine Landau

Morven Leese

Cluster analysis comprises a range of methods of classifying multivariate data into subgroups and these techniques are widely applicable. This new edition incorporates material covering developing areas such as Bayesian statistics & neural networks.

Cluster Analysis

The main message of this book is that people should be on their guard against both scare stories about risks to health, and claims for miracle cures of medical conditions. In the 21st century hardly a day passes without another article appearing in the media about a new treatment for a particular disease, new ways of improving our health by changing our lifestyle or new foodstuffs that claim to increase (or decrease) the risk of heart disease, cancer and the like. But how should the general public react to such claims, given that some of the journalists writing them focus on the sensational rather than the mundane and often have no qualms about sacrificing accuracy and honesty for the sake of a good story? Perhaps the wisest initial response is one of healthy scepticism, followed by an attempt to discover more about the details of the studies behind the reports. But most people are not, and have little desire to become experts in health research. By reading this book, however, these non-experts can, with minimal effort, learn enough about the scientific method to differentiate between those health claims, warnings and lifestyle recommendations that have some merit and those that are unproven or simply dishonest. So if you want to know if ginseng can really help with your erectile dysfunction, if breast cancer screening is all that politicians claim it to be, if ECT for depression is really a horror treatment and should be banned, if using a mobile phone can lead to brain tumours and how to properly evaluate the evidence from health and lifestyle related studies, then this is the book for you.

Separating the Truth from the Myth with Statistics

Health and Lifestyle

Torsten Hothorn

A Proven Guide for Easily Using R to Effectively Analyze Data Like its bestselling predecessor, A Handbook of Statistical Analyses Using R, Second Edition provides a guide to data analysis using the R system for statistical computing. Each chapter includes a brief account of the relevant statistical background, along with appropriate references. New to the Second Edition New chapters on graphical displays, generalized additive models, and simultaneous inference A new section on generalized linear mixed models that completes the discussion on the analysis of longitudinal data where the response variable does not have a normal distribution New examples and additional exercises in several chapters A new version of the HSAUR package (HSAUR2), which is available from CRAN This edition continues to offer straightforward descriptions of how to conduct a range of statistical analyses using R, from simple inference to recursive partitioning to cluster analysis. Focusing on how to use R and interpret the results, it provides students and researchers in many disciplines with a self-contained means of using R to analyze their data.

A Handbook of Statistical Analyses Using R, Second Edition

Like the best-selling first two editions, A Handbook of Statistical Analyses using R, Third Edition provides an up-to-date guide to data analysis using the R system for statistical computing. The book explains how to conduct a range of statistical analyses, from simple inference to recursive partitioning to cluster analysis.New to the Third Edition

A Handbook of Statistical Analyses using R

Stephen George

David Machin

Simon Day

Sylvan Green

A comprehensive volume on clinical trials that covers all important disease and therapeutic areas together with methodologies, phase I/II/III studies and other issues. The volume catalogues the impact of clinical trials on the practice of medicine and discusses the developments and practice of medical statistics. Cancer, cardiovascular disease, dermatological, dental, mental, ophthalmic health, gynaecology and respiratory diseases are all discussed in separate chapters, with discussions on outcome measures, competing risks and statistical models given for each therapy area. It also presents: * A history of clinical trials * A summary of pertinent statistical issues * How to choose a clinical trial design * Ethical constraints and considerations * Clinical trial issues in paediatrics and those involving older patients * Clinical trials in complementary medicine

Textbook of Clinical Trials

A Handbook of Statistical Analyses Using SPSS clearly describes how to conduct a range of univariate and multivariate statistical analyses using the latest version of the Statistical Package for the Social Sciences, SPSS 11. Each chapter addresses a different type of analytical procedure applied to one or more data sets, primarily from the social and behavioral sciences areas. Each chapter also contains exercises relating to the data sets introduced, providing readers with a means to develop both their SPSS and statistical skills. Model answers to the exercises are also provided. Readers can download all of the data sets from a companion Web site furnished by the authors.

Brian S. Everitt

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