Mental illness is many things at once: It is a natural phenomenon that is also shaped by society and culture. It is biological but also behavioral and social. Mental illness is a problem of both the brain and the mind, and this ambiguity presents a challenge for those who seek to accurately classify psychiatric disorders. The leading resource we have for doing so is the American Psychiatric Association's Diagnostic and Statistical Manual, but no edition of the manual has provided a decisive solution, and all have created controversy. In The Diagnostic System, the sociologist Jason Schnittker looks at the multiple actors involved in crafting the DSM and the many interests that the manual hopes to serve. Is the DSM the best tool for defining mental illness? Can we insure against a misleading approach? Schnittker shows that the classification of psychiatric disorders is best understood within the context of a system that involves diverse parties with differing interests. The public wants a better understanding of personal suffering. Mental-health professionals seek reliable and treatable diagnostic categories. Scientists want definitions that correspond as closely as possible to nature. And all parties seek definitive insight into what they regard as the right target. Yet even the best classification system cannot satisfy all of these interests simultaneously. Progress toward an ideal is difficult, and revisions to diagnostic criteria often serve the interests of one group at the expense of another. Schnittker urges us to become comfortable with the socially constructed nature of categorization and accept that a perfect taxonomy of mental-health disorders will remain elusive. Decision making based on evolving though fluid understandings is not a weakness but an adaptive strength of the mental-health profession, even if it is not a solid foundation for scientific discovery or a reassuring framework for patients.

What is it that drives people to undertake music research? Such interest frequently grows from on-the-ground experiences as learners, performers, facilitators, composers, arts administrators, and educators. It can emerge, for example, from music teachers trying out new teaching methods, performers wishing to know more about how to improvise effectively, educators pursuing the most effective ways to structure music curricula, musicians aiming to explain why their music enhances wellbeing among different groups of people, and orchestral managers seeking to promote and protect the health of their players. At the heart of all of these enquiries lies a question of some sort, and it is these research questions that determine the direction of the research to be undertaken. Performing Music Research is a comprehensive guide to planning, conducting, analyzing, and communicating research in music performance. The book examines the approaches and strategies that underpin research in music education, psychology, and performance science. It reviews the knowledge and skills needed to critique existing studies in these fields and to design and carry out new investigations. Perspectives on qualitative, quantitative, and multistrategy methodologies are highlighted across the book in ways that help aspiring researchers bring precision to their research questions, select methods that are appropriate for addressing their questions, and apply those methods systematically and rigorously. Each chapter contains a study guide, comprising a chapter summary, a list of keywords, and suggestions for further discussion, and the book concludes with a resources section, including a glossary and supplementary material to support advanced statistical analysis. The book''s companion website provides information designed to facilitate access to original research and to test knowledge and understanding.

Longitudinal Analysis provides an accessible, application-oriented treatment of introductory and advanced linear models for within-person fluctuation and change. Organized by research design and data type, the text uses in-depth examples to provide a complete description of the model-building process. The core longitudinal models and their extensions are presented within a multilevel modeling framework, paying careful attention to the modeling concerns that are unique to longitudinal data. Written in a conversational style, the text provides verbal and visual interpretation of model equations to aid in their translation to empirical research results. Overviews and summaries, boldfaced key terms, and review questions will help readers synthesize the key concepts in each chapter. "

Written for non-mathematically-oriented readers, this text features:

• "
• A description of the data manipulation steps required prior to model estimation so readers can more easily apply the steps to their own data
• An emphasis on how the terminology, interpretation, and estimation" "of familiar general linear models relates to those of more complex models for longitudinal data
• Integrated model comparisons, effect sizes, and statistical inference in each example to strengthen readers understanding of the overall model-building process
• Sample results sections for each example to provide useful templates for published reports
• Examples using both real and simulated data in the text, along with syntax and output for SPSS, SAS, STATA, and M"plus" at www.PilesOfVariance.com to help readers apply the models to their own data

The book opens with the building blocks of longitudinal analysis general ideas, the general linear model for between-person analysis, and between- and within-person models for the variance and the options within repeated measures analysis of variance. Section 2 introduces "unconditional "longitudinal models including alternative covariance structure models to describe within-person fluctuation over time and random effects models for within-person change. "Conditional "longitudinal models are presented in section 3, including both time-invariant and time-varying predictors. Section 4 reviews advanced applications, including alternative metrics of time in accelerated longitudinal designs, three-level models for multiple dimensions of within-person time, the analysis of individuals in groups over time, and repeated measures designs not involving time. The book concludes with additional considerations and future directions, including an overview of sample size planning and other model extensions for non-normal outcomes and intensive longitudinal data.

Class-tested at the University of Nebraska-Lincoln and in intensive summer workshops, this is an ideal text for graduate-level courses on longitudinal analysis or general multilevel modeling taught in psychology, human development and family studies, education, business, and other behavioral, social, and health sciences. The book s accessible approach will also help those trying to learn on their own. Only familiarity with general linear models (regression, analysis of variance) is needed for this text."

Presenting a new frame of reference, the author argues that Freud's theories are not the result of his genius alone but were developed in exchange with colleagues and students, which is not always apparent at first glance. Replete with examples, the author reconstructs who the theories were addressed to and the discursive context they originally belonged to, thus presenting fresh and surprising readings of Freud's oeuvre. The book also offers a glimpse into Freud's practice. For the first time, Freud's patient record books which he kept for ten years, are being reviewed, offering readers the hard facts about the length and frequency of Freud's analyses.

The new edition of An Introduction to Statistical Concepts is designed to help students really understand statistical concepts, the situations in which they can be used, and how to apply them to data. Hahs-Vaughn and Lomax discuss the most popular, along with many of the lesser-known, procedures and models, whilst also exploring nonparametric procedures used when standard assumptions are violated. They provide in-depth coverage of testing assumptions and highlight several online tools for computing statistics (e.g., effect sizes and their confidence intervals and power). This comprehensive, flexible, and accessible text includes a new chapter on mediation and moderation; expanded coverage of effect sizes; and discussions of sensitivity, specificity, false positive, and false negative, along with using the receiver operator characteristic (ROC) curve. In addition to instructions and screen shots for using SPSS, new to this edition is annotated script for using R. This book, noted for its crystal-clear explanations, and its inclusion of only the most crucial equations, is an invaluable resource for students undertaking a course in statistics in any number of social science and behavioral disciplines-from education, business, communication, exercise science, psychology, sociology and more.

*What do advanced statistical techniques do? *When is it appropriate to use them? *How are they carried out and reported? There are a variety of statistical techniques used to analyse quantitative data that masters students, advanced undergraduates and researchers in the social sciences are expected to be able to understand and undertake. This book explains these techniques, when it is appropriate to use them, how to carry them out and how to write up the results. Most books which describe these techniques do so at too advanced or technical a level to be readily understood by many students who need to use them. In contrast the following features characterise this book: - concise and accessible introduction to calculating and interpreting advanced statistical techniques - use of a small data set of simple numbers specifically designed to illustrate the nature and manual calculation of the most important statistics in each technique - succinct illustration of writing up the results of these analyses - minimum of mathematical, statistical and technical notation - annotated bibliography and glossary of key concepts Commonly used software is introduced, and instructions are presented for carrying out analyses and interpreting the output using the computer programs of SPSS Release 11 for Windows and a version of LISREL 8.51, which is freely available online. Designed as a textbook for postgraduate and advanced undergraduate courses across the socio-behavioural sciences, this book will also serve as a personal reference for researchers in disciplines such as sociology and psychology.

Applauded for its clarity, this accessible introduction helps readers apply multilevel techniques to their research. The book also includes advanced extensions, making it useful as both an introduction for students and as a reference for researchers. Basic models and examples are discussed in nontechnical terms with an emphasis on understanding the methodological and statistical issues involved in using these models. The estimation and interpretation of multilevel models is demonstrated using realistic examples from various disciplines including psychology, education, public health, and sociology. Readers are introduced to a general framework on multilevel modeling which covers both observed and latent variables in the same model, while most other books focus on observed variables. In addition, Bayesian estimation is introduced and applied using accessible software.

STATISTICAL METHODS FOR PSYCHOLOGY, 8E, International Edition surveys the statistical techniques commonly used in the behavioral and social sciences, especially psychology and education. To help students gain a better understanding of the specific statistical hypothesis tests that are covered throughout the text, author David Howell emphasize conceptual understanding. Along with significantly updated discussions of effect size and meta-analysis, this Eighth Edition continues to focus on two key themes that are the cornerstones of this book's success: the importance of looking at the data before beginning a hypothesis test, and the importance of knowing the relationship between the statistical test in use and the theoretical questions being asked by the experiment.

Written by an international team of experts, this collection provides a comprehensive account of established and emerging methods of collecting and analysing data within the framework of personal construct theory.

Covers methods such as content analysis scales, repertory grid methodology, narrative assessments and drawings, the laddering and ABC techniques, and discusses how and why they are usedExplores both qualitative and quantitative methods, as well as methods used in clinical and counselling settingsIncludes 13 contributions from leading international scholars

Conducting Research in Psychology: Measuring the Weight of Smoke provides students an engaging introduction to psychological research by employing humor, stories, and hands-on activities. Through its methodology exercises, learners are encouraged to use their intuition to understand research methods and apply basic research principles to novel problems. Authors Brett W. Pelham and Hart Blanton integrate cutting-edge topics, including implicit biases, measurement controversies, online data collection, and new tools for determining the replicability of a set of research findings. The Fifth Edition broadens its coverage of methodologies to reflect the types of research now conducted by psychologists. Two new chapters accommodate the needs of instructors who incorporate student research projects into their courses.

This book fills a gap in international literature by providing critical reviews on variables of organizational behavior and the main psychological instruments developed to measure them. Measuring instruments developed with theoretical and methodological rigor in the field of Organizational and Work Psychology can contribute to the development of diagnostic analyses to enable organizations to implement the evidence-based changes required for their survival. These changes demand diagnoses based on precise assessments of organizational and individual variables, but many times the professionals responsible for conducting these assessments are not sure of what is the best measuring instrument available. This book is intended to serve as a guide to these professionals. The volume is divided in two parts. The first part brings together chapters dedicated to the following micro-organizational variables: Job Crafting, reactions to organizational change, Psychological Wellbeing at Work, Bridge Employment Assessment in the Work-Retirement Transition, Resilience at Work, and Leadership in Organizations. The second part presents the state-of-the-art of research on the following macro-organizational constructs: Quality of Life at Work, Organizational Climate for Creativity, Values and Organizations, Assessments of Organizational Support, and Contributions by Social Networks Analysis and Organizational Effectiveness. The last chapter presents a critical discussion about the nature and future of organization behavior measuring. Assessing Organizational Behaviors: A Critical Analysis of Measuring Instruments is intended to help market professionals select the diagnostic instruments that best fit into their organizational reality in order to correctly assess organizational behavior. The book will also be of interest to researchers and students in the field of Organizational and Work Psychology as it provides comprehensive overviews of a wide range of instruments developed to measure different variables of organizational behavior.

This practical guide explains the use of randomization tests and provides example designs and macros for implementation in IBM SPSS and Excel. It reviews the theory and practice of single-case and small-n designs so readers can draw valid causal inferences from small-scale clinical studies. The macros and example data are provided on the book s website so that users can run analyses of the text data as well as data from their own studies.

The new edition features:

• More explanation as to why randomization tests are useful and how to apply them.
• More varied and expanded examples that demonstrate the use of these tests in education, clinical work and psychology.
• A website with the macros and datasets for all of the text examples in IBM SPSS and Excel.
• Exercises at the end of most chapters that help readers test their understanding of the material.
• A new glossary that defines the key words that appear in italics when they are first introduced.
• A new appendix that reviews the basic skills needed to do randomization tests.
• New appendices that provide annotated SPSS and Excel macros to help readers write their own or tinker with the ones provided in the book.

The book opens with an overview of single case and small n designs -- why they are needed and how they differ from descriptive case studies. Chapter 2 focuses on the basic concepts of randoization tests. Next how to choose and implement a randomization design is reviewed including material on how to perform the randomizations, how to select the number of observations, and how to record the data. Chapter 5 focuses on how to analyze the data including how to use the macros and understand the results. Chapter 6 shows how randomization tests fit into the body of statistical inference. Chapter 7 discusses size and power. The book concludes with a demonstration of how to edit or modify the macros or use parts of them to write your own.

Ideal as a text for courses on single-case, small n design, and/or randomization tests taught at the graduate level in psychology (especially clinical, counseling, educational, and school), education, human development, nursing, and other social and health sciences, this inexpensive book also serves as a supplement in statistics or research methods courses. Practitioners and researchers with an applied clinical focus also appreciate this book s accessible approach. An introduction to basic statistics, SPSS, and Excel is assumed.

This is the first book to introduce the new statistics - effect sizes, confidence intervals, and meta-analysis - in an accessible way. It is chock full of practical examples and tips on how to analyze and report research results using these techniques. The book is invaluable to readers interested in meeting the new APA Publication Manual guidelines by adopting the new statistics - which are more informative than null hypothesis significance testing, and becoming widely used in many disciplines. Accompanying the book is the Exploratory Software for Confidence Intervals (ESCI) package, free software that runs under Excel and is accessible at www.thenewstatistics.com. The book's exercises use ESCI's simulations, which are highly visual and interactive, to engage users and encourage exploration. Working with the simulations strengthens understanding of key statistical ideas. There are also many examples, and detailed guidance to show readers how to analyze their own data using the new statistics, and practical strategies for interpreting the results. A particular strength of the book is its explanation of meta-analysis, using simple diagrams and examples. Understanding meta-analysis is increasingly important, even at undergraduate levels, because medicine, psychology and many other disciplines now use meta-analysis to assemble the evidence needed for evidence-based practice. The book's pedagogical program, built on cognitive science principles, reinforces learning: Boxes provide "evidence-based" advice on the most effective statistical techniques. Numerous examples reinforce learning, and show that many disciplines are using the new statistics. Graphs are tied in with ESCI to make important concepts vividly clear and memorable. Opening overviews and end of chapter take-home messages summarize key points. Exercises encourage exploration, deep understanding, and practical applications. This highly accessible book is intended as the core text for any course that emphasizes the new statistics, or as a supplementary text for graduate and/or advanced undergraduate courses in statistics and research methods in departments of psychology, education, human development , nursing, and natural, social, and life sciences. Researchers and practitioners interested in understanding the new statistics, and future published research, will also appreciate this book. A basic familiarity with introductory statistics is assumed.

This research volume serves as a comprehensive resource for psychophysiological research on media responses. It addresses the theoretical underpinnings, methodological techniques, and most recent research in this area. It goes beyond current volumes by placing the research techniques within a context of communication processes and effects as a field, and demonstrating how the real-time measurement of physiological responses enhances and complements more traditional measures of psychological effects from media.

This volume introduces readers to the theoretical assumptions of psychophysiology as well as the operational details of collecting psychophysiological data. In addition to discussing specific measures, it includes brief reviews of recent experiments that have used psychophysiological measures to study how the brain processes media. It will serve as a valuable reference for media researchers utilizing these methodologies, or for other researchers needing to understand the theories, history, and methods of psychophysiological research.

This is the first book to introduce the new statistics - effect sizes, confidence intervals, and meta-analysis - in an accessible way. It is chock full of practical examples and tips on how to analyze and report research results using these techniques. The book is invaluable to readers interested in meeting the new APA Publication Manual guidelines by adopting the new statistics - which are more informative than null hypothesis significance testing, and becoming widely used in many disciplines. Accompanying the book is the Exploratory Software for Confidence Intervals (ESCI) package, free software that runs under Excel and is accessible at www.thenewstatistics.com. The book's exercises use ESCI's simulations, which are highly visual and interactive, to engage users and encourage exploration. Working with the simulations strengthens understanding of key statistical ideas. There are also many examples, and detailed guidance to show readers how to analyze their own data using the new statistics, and practical strategies for interpreting the results. A particular strength of the book is its explanation of meta-analysis, using simple diagrams and examples. Understanding meta-analysis is increasingly important, even at undergraduate levels, because medicine, psychology and many other disciplines now use meta-analysis to assemble the evidence needed for evidence-based practice. The book's pedagogical program, built on cognitive science principles, reinforces learning: Boxes provide "evidence-based" advice on the most effective statistical techniques. Numerous examples reinforce learning, and show that many disciplines are using the new statistics. Graphs are tied in with ESCI to make important concepts vividly clear and memorable. Opening overviews and end of chapter take-home messages summarize key points. Exercises encourage exploration, deep understanding, and practical applications. This highly accessible book is intended as the core text for any course that emphasizes the new statistics, or as a supplementary text for graduate and/or advanced undergraduate courses in statistics and research methods in departments of psychology, education, human development , nursing, and natural, social, and life sciences. Researchers and practitioners interested in understanding the new statistics, and future published research, will also appreciate this book. A basic familiarity with introductory statistics is assumed.

Anyone in a helping profession-including professional counselors, spiritual directors, pastoral counselors, chaplains and others-needs to develop effective communication skills. But learning these skills is like learning a new language: it takes time and practice to communicate effectively, and lack of practice can lead to the loss of one's ability to use this new language. Suitable for both beginning students and seasoned practitioners, Skills for Effective Counseling provides a biblically integrated approach to foundational counseling skills that trains the reader to use specific microskills. These skills include perceiving, attending, validating emotion and empathic connection. Chapters include textbook features such as sample session dialogues, role plays and a variety of both in-class and out-of-class exercises and reflection activities that will engage various learning styles. Strategically interwoven throughout the chapters are special topics related to: multicultural counseling biblical/theological applications current and seminal research related to microskills diagnostic and theoretical implications clinical tips for using skills in "real world" counseling settings the relevance of specific microskills to interpersonal relationships and broader ministry settings This textbook and the accompanying IVP Instructor Resources include all of the activities and assignments that an instructor might need to execute a graduate, undergraduate or lay course in foundational counseling skills. Professors teaching within CACREP-accredited professional counseling programs will be able to connect specific material in the textbook to the latest CACREP Standards. Christian Association for Psychological Studies (CAPS) Books explore how Christianity relates to mental health and behavioral sciences including psychology, counseling, social work, and marriage and family therapy in order to equip Christian clinicians to support the well-being of their clients.

Rolf Steyer, Autor des erfolgreichen Lehrbuchs "Messen und Testen," schliesst mit diesem Buch die Kluft zwischen Regressionstheorie und deren empirischer Anwendung, der Regressionsanalyse.
Grundbegriffe der Statistik werden ohne Bezug zu komplizierten Stichprobenmodellen erlautert. Neben der Regressionsanalyse konnen auch verschiedene statistische Verfahren, wie die Varianz- oder Faktorenanalyse, als Spezialfalle regressiver Abhangigkeiten angesehen werden. Das Studium der Regressionstheorie dient daher dem Verstandnis grundlegender statistischer Verfahren in der Psychologie."

The Fourth Edition of Statistics: A Gentle Introduction shows students that an introductory statistics class doesn't need to be difficult or dull. This text minimizes students' anxieties about math by explaining the concepts of statistics in plain language first, before addressing the math. Each formula within the text has a step-by-step example to demonstrate the calculation so students can follow along. Only those formulas that are important for final calculations are included in the text so students can focus on the concepts, not the numbers. A wealth of real-world examples and applications gives a context for statistics in the real world and how it helps us solve problems and make informed choices. New to the Fourth Edition are sections on working with big data, new coverage of alternative non-parametric tests, beta coefficients, and the "nocebo effect," discussions of p values in the context of research, an expanded discussion of confidence intervals, and more exercises and homework options under the new feature "Test Yourself." Included with this title: The password-protected Instructor Resource Site (formally known as SAGE Edge) offers access to all text-specific resources, including a test bank and editable, chapter-specific PowerPoint (R) slides.

Everyone is on a journey of growth, from birth to death. The authors used their research data, to tap into the vital stages of this journey of growth from a psychological growth perspective. They linked the stages of psychological growth to self-leadership development. Additionally, they linked different stages of self-leadership development to different types and styles of leadership. For example, they found that authoritative leadership is linked to earlier stages of psychological growth, while inclusive leadership is linked to latter stages of psychological growth.

The Poetic Journey of Self-Leadership: Leadership Development along Stages of Psychological Growth is relevant to those interested in self-reflection (as it assists to assign oneself to a stage of psychological development), personal growth (as it anticipates processes to follow during one’s current stage of development), self-leadership development, as well as useful for leadership assessment by practitioners (by assigning leadership to stages of development). Additionally, from an academic perspective, the book is relevant to psychology, sociology and leadership students.

Contents include:

• Surviving: Abandonment versus overwhelment; Survival-stage leader
• Conforming: Internality versus externality; Conforming leader
• Differentiating: Social predestination; Differentiated leader
• Individuating: Guilt versus fear; Journey to individuation; Conquering complexes; Authenticity; Individuated leader
• Self-actualizing: Kintsugi; Traumas; Magical other; Self-actualised leader
• Integrating: Values; Heroes; Purpose; Integrated leader
• Serving: Servant leader

Books about leadership and poetry are mostly written from the perspective of leaders, but The Poetic Journey of Self-Leadership: Leadership Development along Stages of Psychological Growth, focuses on self-leadership development, and not the usual listing of heroic leader capabilities that must be strived for. The authors used self-reported poetry from diverse participants, and in their own voices as their main data collection source. The book presents a diversity of writing styles and topics, and makes it much wider in scope and richer than other books.

Providing a practical, thorough understanding of how factor analysis works, Foundations of Factor Analysis, Second Edition discusses the assumptions underlying the equations and procedures of this method. It also explains the options in commercial computer programs for performing factor analysis and structural equation modeling. This long-awaited edition takes into account the various developments that have occurred since the publication of the original edition.

New to the Second Edition

• A new chapter on the multivariate normal distribution, its general properties, and the concept of maximum-likelihood estimation
• More complete coverage of descriptive factor analysis and doublet factor analysis
• A rewritten chapter on analytic oblique rotation that focuses on the gradient projection algorithm and its applications
• Discussions on the developments of factor score indeterminacy
• A revised chapter on confirmatory factor analysis that addresses philosophy of science issues, model specification and identification, parameter estimation, and algorithm derivation

Presenting the mathematics only as needed to understand the derivation of an equation or procedure, this textbook prepares students for later courses on structural equation modeling. It enables them to choose the proper factor analytic procedure, make modifications to the procedure, and produce new results.

Diary Methods, sometimes known as intensive repeated measures or ecological assessments, are an important method for social and personality psychologists. The volume begins with a rationale for such methods, with an emphasis on social and personality psychology, and then provides a non-technical, accessible description of how to use such methods, including advice on study design, data analysis, and preparation of papers. Both interval contingent methods (e.g., daily diaries) and event contingent methods (e.g., social interaction diaries) are covered. The author, John B. Nezlek, has used these methods in his own scholarly work for over 30 years and has written this book to provide an introduction to these methods for those who are not familiar with them. This book will be perfect for advanced students and researchers in social and personality psychology and related disciplines who use and want to use diary methods in their research. The SAGE Library of Methods in Social and Personality Psychology is a new series of books launching in early 2011 to provide students and researchers with an understanding of the methods and techniques essential to conducting cutting-edge research. Each volume explains a specific topic and has been written by an active scholar (or scholars) with expertise in that particular methodological domain. Assuming no prior knowledge of the topic, the volumes are clear and accessible for all readers. In each volume, a topic is introduced, applications are discussed, and readers are led step by step through worked examples. In addition, advice about how to interpret and prepare results for publication are presented. The Library should be particularly valuable for advanced students and academics who want to know more about how to use research methods in social and personality psychology.

For many years the Handbook of Methods in Nonverbal Behavior Research (Scherer & Ekman, 1982) has been an invaluable text for researchers looking for methods to study nonverbal behavior and the expression of affect. A successor to this essential text, The New Handbook of Methods in Nonverbal Behavior Research includes chapters on coding and methodological issues for a variety of areas in nonverbal behavior: facial actions, vocal behavior, and body movement. Issues relevant to judgment studies, methodology, reliability, analyses, etc. have also been updated. The topics are broad and include specific information about methodology and coding strategies in education, psychotherapy, deception, nonverbal sensitivity, and marital and group behavior. There is also a chapter detailing specific information on the technical aspects of recording the voice and face, and specifically in relation to deception studies.
This volume will be valuable for both new researchers and those already working in the fields of nonverbal behavior, affect expression, and related topics. It will play a central role in further refining research methods and coding strategies, allowing a comparison of results from various laboratories where research on nonverbal behavior is being conducted. This will advance research in the field and help to coordinate results so that a more comprehensive understanding of affect expression can be developed.

Intended to bridge the gap between the latest methodological developments and cross-cultural research, this interdisciplinary resource presents the latest strategies for analyzing cross-cultural data. Techniques are demonstrated through the use of applications that employ cross-national data sets such as the latest European Social Survey. With an emphasis on the generalized latent variable approach, internationally prominent researchers from a variety of fields explain how the methods work, how to apply them, and how they relate to other methods presented in the book. Syntax and graphical and verbal explanations of the techniques are included. Online resources, available at www.routledge.com/9781138690271, include some of the data sets and syntax commands used in the book. Applications from the behavioral and social sciences that use real data-sets demonstrate: The use of samples from 17 countries to validate the resistance to change scale across these nations How to test the cross-national invariance properties of social trust The interplay between social structure, religiosity, values, and social attitudes A comparison of anti-immigrant attitudes and patterns of religious orientations across European countries. The second edition includes six new chapters and two revised ones presenting exciting developments in the literature of cross-cultural analysis including topics such as approximate measurement invariance, alignment optimization, sensitivity analyses, a mixed-methods approach to test for measurement invariance, and a multilevel structural equation modeling approach to explain noninvariance. This book is intended for researchers, practitioners, and advanced students interested in cross-cultural research. Because the applications span a variety of disciplines, the book will appeal to researchers and students in: psychology, political science, sociology, education, marketing and economics, geography, criminology, psychometrics, epidemiology, and public health, as well as those interested in methodology. It is also appropriate for an advanced methods course in cross-cultural analysis.

This fresh, new textbook provides a thorough and student-friendly guide to the different techniques used in cognitive neuroscience. Given the breadth of neuroimaging techniques available today, this text is invaluable, serving as an approachable text for students, researchers, and writers. This text provides the right level of detail for those who wish to understand the basics of neuroimaging and also provides more advanced material in order to learn further about particular techniques. With a conversational, student-friendly writing style, Aaron Newman introduces the key principles of neuroimaging techniques, the relevant theory and the recent changes in the field.