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Describes various commonly used methods of initial factoring and factor rotation. In addition to a full discussion of exploratory factor analysis, confirmatory factor analysis and various methods of constructing factor scales are also presented.
Dieses Buch führt ein in die grundlegenden Ansätze des Clusterns, Segmentierens und der Faktorextraktion. Kapitel 1 behandelt die Familie der Clusteranalysen. Darin vorgestellt werden u.a. hierarchische, partitionierende, sowie das TwoStep Cluster-Verfahren. Kapitel 2 behandelt die Gruppe der Faktorenanalysen. Zuerst wird in das Grundprinzip und dann in die Varianten der Faktorenanalyse (z.B. Alpha, Hauptfaktoren, Hauptkomponenten), die wichtigsten Extraktions-, wie auch Rotationsmethoden (z.B. orthogonal vs. oblique) eingeführt. Kapitel 3 stellt die Diskriminanzanalyse vor. Weitere Kapitel stellen Möglichkeiten des Clusterns und Segmentieren mit CLEMENTINE vor, u.a. Entscheidungsbäume und ausgewählte Cluster-Knoten.
How do we group different subjects on a variety of variables? Should we use a classification procedure in which only the concepts are classified (typology), one in which only empirical entities are classified (taxonomy), or a combination of both? Kenneth D Bailey addresses these questions and shows how classification methods can be used to improve research. Beginning with an exploration of the advantages and disadvantages of classification procedures, the book covers topics such as: clustering procedures including agglomerative and divisive methods; the relationship among various classification techniques; how clustering methods compare with related statistical techniques; classification resources; and software packages fo
David de Vaus' classic text Surveys in Social Research provides clear advice on how to plan, conduct and analyse social surveys. It emphasises the links between theory and research, the logic and interpretation of statistics and the practices of social research. This sixth edition has been completely revised and updated, and contains new examples, data and extensive lists of web resources. As well as explaining how to conduct good surveys, de Vaus shows how to become a critical consumer of research. He argues that the logic of surveys and statistics is simply an extension of the logic we use in everyday life; analysis, however, requires creativity and imagination rather than the application of sterile mechanical procedures. The prime goal of research should be to gain accurate understanding and, as a researcher, use methods and techniques which enhance understanding. De Vaus advocates researchers use the method, rather than letting the method use you. Surveys in Social Research is essential reading for students and researchers working with surveys. It assumes no background in statistical analysis, and gives you the tools you need to come to grips with this often challenging field of work.
The new edition of this critically praised textbook continues to provide the most comprehensive overview of the concepts, methods, and research advances in the field; particularly the application of molecular genomics and of neuroimaging. It has been revised and enhanced to capitalize on the strengths of the first and second editions while keeping it up-to-date with the field of psychiatry and epidemiology. This comprehensive publication now includes chapters on experimental epidemiology, gene-environment interactions, the use of case registries, eating disorders, suicide, childhood disorders and immigrant populations, and the epidemiology of a number of childhood disorders. As in the first and second editions, the objective is to provide a comprehensive, easy to understand overview of research methods for the non-specialist. The book is ideal for students of psychiatric epidemiology, psychiatric residents, general psychiatrists, and other mental health professionals. The book features a new editor, Peter Jones, from the University of Cambridge, who joins the successful US team of Ming Tsuang and Mauricio Tohen.
Statistical Concepts, 3/e consists of the last 8 chapters of Richard Lomax’s best selling text, An Introduction to Statistical Concepts, 2/e. Designed for a second course in statistics, Lomax’s comprehensive and flexible coverage allows instructors to pick and choose those topics most appropriate for their course. It includes topics not found in competing texts such as the non-parametric and modern alternative procedures and advanced analysis of variance (ANOVA) and regression models. Its intuitive approach helps students more easily understand the concepts and interpret software results. Throughout the text, the author demonstrates how many statistical concepts relate to one another. Only the most crucial equations are included. The new edition features: SPSS sections throughout with input, output, and APA style write-ups using the book’s dataset a CD with every example and problem dataset used in the text in SPSS format more information on confidence intervals, effect size measures, power, and regression models a revised sequence of the regression and ANOVA chapters for enhanced conceptual flow de-emphasized computations to provide more discussion of concepts and software more problems with more realistic data and a greater emphasis on interpretation an Instructor’s Resource CD with all of the solutions to the problems and other teaching aids. Statistical Concepts, 3/e covers a number of ANOVA and regression models: one-factor; multiple comparison; factorial; ANCOVA; random- and mixed-effect; hierarchical and randomized blocks; and simple and multiple regression. Realistic examples from education and the behavioral sciences illustrate the concepts. Each example includes an examination of the various procedures and necessary assumptions, tips on developing an APA style write-up, and sample SPSS output. Useful tables of assumptions and the effects of their violation are included, along with how to test assumptions in SPSS. Each chapter concludes with conceptual and computational problems, about a third of which are new to this edition. Answers to the odd-numbered problems are provided. Intended for the second or intermediate course in statistics taught in education and/or behavioral science departments usually found at the master’s or doctoral level and occasionally at the undergraduate level. A prerequisite of descriptive statistics through t-tests is assumed.

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