This book describes the exploratory use of data analysis. The importance of searching for patterns in data is stressed through many worked examples. The interpretation of the output from statistical software is also emphasized. This up-to-date text includes modern techniques such as multidimensional scaling, cluster analysis, generalized linear models and structural equation models. Part I explains data types and the statistical knowledge required to use the book. Part II explains which methods to use. The final parts cover the analysis of variables in more detail. This outstanding volume will prove useful as a reference for statisticians, and valuable to advanced undergraduates and graduate students in fields such as psychology, sociology, economics, and medicine, or in other areas where quantitative methods are central.

Applied Multivariate Data Analysis

Science & Math

Everitt, Brian S.

Dunn, Graham

Mathematics

Oxford University Press

Statistics play a major role in psychological research. However, there is no text which bridges the gap between the very general introductory books and the highly technical research-level studies. Making Sense of Statistics in Psychology fills this need, with the added advantages of examples and data sets relevant to actual problems in behavioral science; an emphasis on graphical presentation; and a focus on computer methods rather than basic arithmetic. A unique feature is the collection of challenging data sets, the majority from actual psychological research. Many of these data sets are also stored on the disk that accompanies the book, thus allowing students to run both the analyses described and their own attempts at extending them. It is also ideal for more experienced researchers who want a quick reference or refresher on statistics.

Making Sense of Statistics in Psychology: A Second-Level Course

Politics & Social Sciences

Social Sciences

Mental health problems account for a quarter of all physician consultations, and place an enormous financial burden on society. For this reason, the search for effective treatments in psychiatry continues apace. But as they are developed, it is essential that we have effective and rigorous methods of assessing the benefits and safety of new treatments. The randomised controlled trial (RCT) is accepted as being the best method for doing this. In order to understand what does and does not work, mental health professionals need to understand how treatments have been assessed and evaluated. Clinical Trials in Psychiatry is the first book to explain RCTs for mental health professionals. It starts by discussing why we need trials and why they are the best way of deciding if a treatment works. It then describes the different types of trials, how to analyze the results, and how to conduct a trial. For anyone working in the mental health field, this book will be an essential source of reference, allowing them to make informed decisions about treatment.

Clinical Trials in Psychiatry

Health, Fitness & Dieting

Wessely, Simon

Psychology & Counseling

Collaborations between statisticians and behavioral scientists can benefit both the design and analysis of a practical research project. In this refreshing book, Brian Everitt and Dale Hay employ a case-oriented approach to demonstrate how such a collaboration works. A case-study drawn from child psychiatry is used to show the statistical techniques available to tackle a range of questions and data.

Talking about Statistics: A Psychologist's Guide to Design and Analysis

Hay, Dale F.

Hodder Education Publishers

This book emphasises the exploratory use of data analysis. Worked examples help the reader to identify and describe patterns in data. Part one explains data types and the statistical knowledge required to use this book, part two explains which methods to use and the final section covers analysis of variables in detail. This book is designed to be of interest to social and behavioural undergraduates as well as Msc students, statisticians and librarians.

Cluster Analysis

This practical text has been reworked to provide an account of the subject of cluster analysis - the generic name for a wide variety of procedures involved with identifying groups within data. By organizing multivariate data into such subgroups clustering may help the investigator discover the characteristics of any structure or pattern present. However, applying the methods in practice requires considerable care and researchers may need guidance in order to avoid misinterpreting results. It offers an applied approach using limited mathematics, contains detailed descriptions of recent methods along with numerous examples and includes information on the software packages available. Other titles by Brian S. Everitt include "Talking About Statistics: A Psychologist's Guide to Design and Analysis" (with Dale F. Hay), "Applied Multivariate Data Analysis" (with Graham Dunn) and "Statistical Methods for Medical Investigations".

Clinical Biostatistics: An Introduction to Evidence-Based Medicine

Biological Sciences

This expanded and updated second edition builds upon the success of its predecessor in providing a concise, practical and yet relatively non-technical account of those more sophisticated statistical techniques now used routinely in many medical investigations. The new edition gives additional space to such important topics as the design of medical investigations, regression and logistic regression, the analysis of longitudinal studies, the problems of missing data, and the analysis of observational studies. All chapters include new examples. Statistical Methods for Medical Investigations is aimed at medical statisticians and other researchers working in the medical field.

Statistical Methods in Medical Investigations

This book is fully updated to include new sections on neural networks, graphical modelling, hierarchical or multilevel modelling, and latent class models. The sections on correspondence analysis and principal components analysis have been expanded. It also offers more exercises for students and an updated review of the available software suited to multivariate analysis. The text avoids irrelevant theoretical statistics and concentrates on enabling the students to understand the concepts behind the data analysis.

Business & Money

Economics

Cluster analysis comprises a range of methods for classifying multivariate data into subgroups. By organising multivariate data into such subgroups, clustering can help reveal the characteristics of any structure or patterns present. These techniques are applicable in a wide range of areas such as medicine, psychology and market research. This fourth edition of the highly successful Cluster Analysis represents a thorough revision of the third edition and covers new and developing areas such as classification likelihood and neural networks for clustering. Real life examples are used throughout to demonstrate the application of the theory, and figures are used extensively to illustrate graphical techniques. The book is comprehensive yet relatively non-mathematical, focusing on the practical aspects of cluster analysis.

Landau, Sabine

Leese, Morven

See the best price to sell, buy, or rent books by Everitt, Brian S.. BookScouter helps to compare book prices from 25+ online bookstores and 30+ buyback vendors with a single search.

Books by Everitt, Brian S.

See the best price to sell, buy, or rent books by Everitt, Brian S.. BookScouter helps to compare book prices from 25+ online bookstores and 30+ buyback vendors with a single search.

Applied Multivariate Data Analysis

Making Sense of Statistics in Psychology: A Second-Level Course

Clinical Trials in Psychiatry

Talking about Statistics: A Psychologist's Guide to Design and Analysis

Applied Multivariate Data Analysis

Cluster Analysis

Clinical Biostatistics: An Introduction to Evidence-Based Medicine

Statistical Methods in Medical Investigations

Applied Multivariate Data Analysis

Cluster Analysis