This book provides a comprehensive overview of research methods in the behavioral sciences, focusing primarily on the conceptual issues inherent in conducting research. It covers topics that are often omitted from other texts, including measurement issues, correlational research, qualitative research, and integrative literature reviews. The book also includes discussions of diversity issues as they related to behavioral science research. New to this edition are chapter boxes that focus on applied issues related to each chapter topic. Throughout the book, readable examples and informative tables and figures are provided. The authors also take a contemporary approach to topics such as research ethics, replication research, and data collection (including internet research).

Drawing on the latest research into memory, information processing and learning, this book helps students to tailor their study techniques to their own particular learning style and psychological make-up. * An exploration of the tools and techniques essential to success in studying and passing examinations. * Suitable for classroom, distance learning, online, or blended learning environments. * Includes questionnaires, activities, key learning points, illustrations, diagrams, flow charts, and mindmaps.

Research Design and Statistical Analysis provides comprehensive coverage of the design principles and statistical concepts necessary to make sense of real data. The book s goal is to provide a strong conceptual foundation to enable readers to generalize concepts to new research situations. Emphasis is placed on the underlying logic and assumptions of the analysis and what it tells the researcher, the limitations of the analysis, and the consequences of violating assumptions. Sampling, design efficiency, and statistical models are emphasized throughout. As per APA recommendations, emphasis is also placed on data exploration, effect size measures, confidence intervals, and using power analyses to determine sample size. "Real-world" data sets are used to illustrate data exploration, analysis, and interpretation. The book offers a rare blend of the underlying statistical assumptions, the consequences of their violations, and practical advice on dealing with them.

Changes in the New Edition:

• Each section of the book concludes with a chapter that provides an integrated example of how to apply the concepts and procedures covered in the chapters of the section. In addition, the advantages and disadvantages of alternative designs are discussed.
• A new chapter (1) reviews the major steps in planning and executing a study, and the implications of those decisions for subsequent analyses and interpretations.
• A new chapter (13) compares experimental designs to reinforce the connection between design and analysis and to help readers achieve the most efficient research study.
• A new chapter (27) on common errors in data analysis and interpretation.
• Increased emphasis on power analyses to determine sample size using the G*Power 3 program.
• Many new data sets and problems.
• More examples of the use of SPSS (PASW) Version 17, although the analyses exemplified are readily carried out by any of the major statistical software packages.
• A companion website with the data used in the text and the exercises in SPSS and Excel formats; SPSS syntax files for performing analyses; extra material on logistic and multiple regression; technical notes that develop some of the formulas; and a solutions manual and the text figures and tables for instructors only.

Part 1 reviews research planning, data exploration, and basic concepts in statistics including sampling, hypothesis testing, measures of effect size, estimators, and confidence intervals. Part 2 presents between-subject designs. The statistical models underlying the analysis of variance for these designs are emphasized, along with the role of expected mean squares in estimating effects of variables, the interpretation of nteractions, and procedures for testing contrasts and controlling error rates. Part 3 focuses on repeated-measures designs and considers the advantages and disadvantages of different mixed designs. Part 4 presents detailed coverage of correlation and bivariate and multiple regression with emphasis on interpretation and common errors, and discusses the usefulness and limitations of these procedures as tools for prediction and for developing theory.

This is one of the few books with coverage sufficient for a 2-semester course sequence in experimental design and statistics as taught in psychology, education, and other behavioral, social, and health sciences. Incorporating the analyses of both experimental and observational data provides continuity of concepts and notation. Prerequisites include courses on basic research methods and statistics. The book is also an excellent resource for practicing researchers."

Items with ordered response categories are common in survey research, such as when respondents are asked how much they agree with certain statements. But how large are the differences between categories of response, and how well do they distinguish between respondents? This volume is the first to introduce the evaluation of rating scales to an audience of survey researchers. Evaluating Rating Scale Functioning for Survey Research provides researchers with an overview of rating scale analysis along with practical guidance on how to conduct such analyses with their own survey data. Author Stefanie A. Wind presents three categories of methods: Rasch models; non-Rasch Item Response Theory (IRT) models; and non-parametric models, together with practical examples. Tutorials, datasets, and software code (R and Facets) to accompany the book are available on the book's website.

*First comprehensive introduction and guide to social fiction, an arts-based research approach. *Part graduate text, part reference for students and researchers in education, sociology, psychology, communications, nursing, human services, and related fields. *Engaging, humorous writing interweaves how-tos with examples from the author's fiction, along with insights and tips. *Provides evaluation criteria for social fiction.

This book provides an overview of cutting-edge methods currently being used in cognitive psychology, which are likely to appear with increasing frequency in coming years. Once built around univariate parametric statistics, cognitive psychology courses now seem deficient without some contact with methods for signal processing, spatial statistics, and machine learning. There are also important changes in analyses of behavioral data (e.g., hierarchical modeling and Bayesian inference) and there is the obvious change wrought by the advancement of functional imaging. This book begins by discussing the evidence of this rapid change, for example the movement between using traditional analyses of variance to multi-level mixed models, in psycholinguistics. It then goes on to discuss the methods for analyses of physiological measurements, and how these methods provide insights into cognitive processing. New Methods in Cognitive Psychology provides senior undergraduates, graduates and researchers with cutting-edge overviews of new and emerging topics, and the very latest in theory and research for the more established topics.

Dieser Buchtitel ist Teil des Digitalisierungsprojekts Springer Book Archives mit Publikationen, die seit den Anfangen des Verlags von 1842 erschienen sind. Der Verlag stellt mit diesem Archiv Quellen fur die historische wie auch die disziplingeschichtliche Forschung zur Verfugung, die jeweils im historischen Kontext betrachtet werden mussen. Dieser Titel erschien in der Zeit vor 1945 und wird daher in seiner zeittypischen politisch-ideologischen Ausrichtung vom Verlag nicht beworben.

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.

"Why Science Matters: Understanding the Methods of Psychological Research "rises above standard research methods texts by presenting an up-to-date view of contemporary psychological science as it is currently understood and practiced.
Explores not only the procedural aspects of psychological research, but also delves into the issue of how to accomplish effective science.
Explicates how hypotheses and theories are to be evaluated.
Suggests that the proper approach to devising and evaluating theories is by abduction, not by induction or deduction alone.
Incorporates new investigatory procedures, current methodologists, conflicts and issues, implications of the philosophy of science, and a lively prose style.
Provides a picture of science that will engage students and expand their abilities as both scientists and psychologists.

Incorporating a hands-on pedagogical approach, Nonparametric Statistics for Social and Behavioral Sciences presents the concepts, principles, and methods used in performing many nonparametric procedures. It also demonstrates practical applications of the most common nonparametric procedures using IBM's SPSS software. This text is the only current nonparametric book written specifically for students in the behavioral and social sciences. Emphasizing sound research designs, appropriate statistical analyses, and accurate interpretations of results, the text: Explains a conceptual framework for each statistical procedure Presents examples of relevant research problems, associated research questions, and hypotheses that precede each procedure Details SPSS paths for conducting various analyses Discusses the interpretations of statistical results and conclusions of the research With minimal coverage of formulas, the book takes a nonmathematical approach to nonparametric data analysis procedures and shows students how they are used in research contexts. Each chapter includes examples, exercises, and SPSS screen shots illustrating steps of the statistical procedures and resulting output.

Meeting a key need for qualitative researchers, this practical book presents tools for creating productive partnerships and managing each phase of a collaborative project. The authors provide guidelines for working across disciplines, status differentials (such as professor and student), and geographical locations. Collaboration within particular qualitative traditions--cross-cultural research, duoethnography, participatory action research, arts-based collaborations, and others--is described and illustrated with exemplars of published studies. Readers learn how to build research teams, formulate research questions, gather and analyze data, and assess how collaborations are working. Ethical questions are highlighted throughout: Who owns collaborative research? Who decides what aspects of the findings should be disseminated? How can inequitable power relations be redressed? Within-chapter "Pedagogical Pathways" sections provide practice exercises and opportunities for reflection.

The "Handbook of Research Methods in Clinical Psychology" presents a comprehensive and contemporary treatment of research methodologies used in clinical psychology. Topics discussed include experimental and quasi-experimental designs, statistical analysis, validity, ethics, cultural diversity, and the scientific process of publishing. Written by leading researchers, the chapters focus on specific applications of research into psychopathology, assessment and diagnosis, therapy, and interventions for both child and adult populations. Special attention is also given to research into professional issues, prevention, and promotion. Research vignettes describe exemplary projects illustrating the essential elements of the research topics. In addition, the editors outline a research agenda for clinical psychologists that demonstrates the exciting future for the field.

This handbook coherently illustrates the range of research methodologies used in clinical psychology and is a vital resource for both students and scholars who wish to expand their knowledge.
Covers basic methodologies as well as specific applications of research designs.
Includes research vignettes that describe exemplary studies and illustrate the essential elements of the research topics.
Contains chapters written by active researchers in the field.
Outlines a research agenda for clinical psychologists that demonstrates the exciting future for the field.
Now available in full text online via xreferplus, the award-winning reference library on the web from xrefer. For more information, visit www.xreferplus.com

Collecting and analyzing data on unemployment, inflation, and inequality help describe the complex world around us. When published by the government, such data are called official statistics. They are reported by the media, used by politicians to lend weight to their arguments, and by economic commentators to opine about the state of society. Despite such widescale use, explanations about how these measures are constructed are seldom provided for a non-technical reader. This Measuring Society book is a short, accessible guide to six topics: jobs, house prices, inequality, prices for goods and services, poverty, and deprivation. Each relates to concepts we use on a personal level to form an understanding of the society in which we live: We need a job, a place to live, and food to eat. Using data from the United States, we answer three basic questions: why, how, and for whom these statistics have been constructed. We add some context and flavor by discussing the historical background. This book provides the reader with a good grasp of these measures. Chaitra H. Nagaraja is an Associate Professor of Statistics at the Gabelli School of Business at Fordham University in New York. Her research interests include house price indices and inequality measurement. Prior to Fordham, Dr. Nagaraja was a researcher at the U.S. Census Bureau. While there, she worked on projects relating to the American Community Survey.

This "Essential Handbook" provides the critical elements from its companion volume, the successful Handbook of Offender Assessment and Treatment. A comprehensive review of assessment and treatment, it covers the major offender groups: sex offenders, violent offenders, offenders with mental and personality disorders, and property offenders. A range of treatment approaches are also included, incorporating behavioural, cognitive, skills-based, anger management, school programmes, and family-based approaches.

Whilst retaining its international, high quality appeal, The Essential Handbook of Offender Assessment and Treatment is a concise, portable edition for all clinicians, academics and researchers working with offenders across a range of settings.

Experience Sampling in Mental Health Research provides comprehensive and user-friendly guidance on when and how to apply this methodology in the assessment of clinical populations. Divided into three sections, the book offers step-by-step instruction on how to design, develop and implement an ESM study, as well as advice on how this approach might be adapted for common mental health difficulties. With an eye to the future of this type of research, the contributors also consider how ESM might be adapted for use as a form of clinical assessment and intervention. Experience Sampling in Mental Health Research combines the knowledge and expertise of leading international experts in the field, and will be helpful for students, researchers and clinicians wishing to start or develop their understanding of this methodology.

Scale Development: Theory and Applications, by Robert F. DeVellis and new co-author Carolyn T. Thorpe, demystifies measurement by emphasizing a logical rather than strictly mathematical understanding of concepts. The Fifth Edition includes a new chapter that lays out the key concepts that distinguish indices from scales, contrasts various types of indices, suggests approaches for developing them, reviews validity and reliability issues, and discusses in broad terms some analytic approaches. All chapters have been updated, and the book strikes a balance between including relevant topics and highlighting recent developments in measurement while retaining an accessible, user-friendly approach to the material covered.

When a person recovers a memory of an event from their past for which they claim little or no previous awareness, how reliable is that memory?

In this refreshing new approach to the problem, Graham Davies and Tim Dalgleish have assembled leading figures from both sides of the debate to provide a balanced overview of the evidence from theoretical and clinical psychologists.

Recovered Memories: Seeking the Middle Ground, unlike most other writing on the topic, eschews extreme positions. It provides clinicians with findings from the latest research to enhance their understanding of memory and presents pure researchers with a range of experiences encountered in clinical practice for which they presently have few explanations.

Organised around three themes, social, evidential and clinical aspects are covered. Topics include the impact on family and community members, the latest findings on implanted memories and discussion of clinical guidelines for therapeutic practice.

This important new collection should not be missed by anyone with an interest in memory, whether engaged in a clinical, legal, child protection, family welfare or experimental research capacity. It is the most authoritative and comprehensive review of the evidence on both sides available to date.

Textual Statistics with R comprehensively covers the main multidimensional methods in textual statistics supported by a specially-written package in R. Methods discussed include correspondence analysis, clustering, and multiple factor analysis for contigency tables. Each method is illuminated by applications. The book is aimed at researchers and students in statistics, social sciences, hiistory, literature and linguistics. The book will be of interest to anyone from practitioners needing to extract information from texts to students in the field of massive data, where the ability to process textual data is becoming essential.

Advances in Motivation Science, Volume Five, is the latest release in this serial on the topic of motivation science. Users will find comprehensive chapters on a variety of topics, including The functional architecture of personality, Parsing the role of mesolimbic dopamine in specific aspects of motivation: Behavioral activation, invigoration, and effort-based decision making, The allostatic brain: Prediction, affect and motivation, the Egosystem and Ecosystem: Motivational Systems for the Self, The Role of Flow in Optimal Development, PSI Theory, Self-Efficacy's Odd Role in Unifying Self-Regulation Theories, Children's Expectancies and Values: Developmental Trajectories and Impact on Performance and Choice, amongst other topics. The advent of the cognitive revolution in the 1960 and 70s eclipsed the emphasis on motivation to a large extent, but in the past two decades motivation has returned en force. Today, motivational analyses of affect, cognition and behavior are ubiquitous across psychological literatures and disciplines. This series brings together internationally recognized experts who focus on cutting-edge theoretical and empirical contributions in this important area of psychology.

The Handbook of Research Methods in Human Memory presents a collection of chapters on methodology used by researchers in investigating human memory. Understanding the basic cognitive function of human memory is critical in a wide variety of fields, such as clinical psychology, developmental psychology, education, neuroscience, and gerontology, and studying memory has become particularly urgent in recent years due to the prominence of a number of neurodegenerative diseases, such as Alzheimer's. However, choosing the most appropriate method of research is a daunting task for most scholars. This book explores the methods that are currently available in various areas of human memory research and serves as a reference manual to help guide readers' own research. Each chapter is written by prominent researchers and features cutting-edge research on human memory and cognition, with topics ranging from basic memory processes to cognitive neuroscience to further applications. The focus here is not on the "what," but the "how"-how research is best conducted on human memory.

Diversity-Sensitive Personality Assessment is a comprehensive guide for clinicians to consider how various aspects of client diversity-ethnicity, gender, sexual orientation, age, nationality, religion, regionalism, socioeconomic status, and disability status-can impact assessment results, interpretation, and feedback. Chapters co-written by leading experts in the fields of diversity and personality assessment examine the influence of clinician, client, interpersonal, and professional factors within the assessment context. This richly informed and clinically useful volume encourages clinicians to delve into the complex ways in which individuals' personal characteristics, backgrounds, and viewpoints intersect. This book fills an important gap in the personality assessment literature and is an essential resource for clinicians looking to move beyond surface-level understandings of diversity in assessment.

Practice-Based Research shows mental-health practitioners how to establish viable and productive research programs in routine clinical settings. Chapters written by experts in practice-based research use real-world examples to help clinicians work through some of the most common barriers to research output in these settings, including lack of access to institutional review boards, lack of organizational support, and limited access to financial resources. Specialized chapters also provide information on research methods and step-by-step suggestions tailored to a variety of practice settings. This is an essential volume for clinicians interested in establishing successful, long-lasting practice-based research programs.

Compositional Data Analysis in Practice is a user-oriented practical guide to the analysis of data with the property of a constant sum, for example percentages adding up to 100%. Compositional data can give misleading results if regular statistical methods are applied, and are best analysed by first transforming them to logarithms of ratios. This book explains how this transformation affects the analysis, results and interpretation of this very special type of data. All aspects of compositional data analysis are considered: visualization, modelling, dimension-reduction, clustering and variable selection, with many examples in the fields of food science, archaeology, sociology and biochemistry, and a final chapter containing a complete case study using fatty acid compositions in ecology. The applicability of these methods extends to other fields such as linguistics, geochemistry, marketing, economics and finance. R Software The following repository contains data files and R scripts from the book https://github.com/michaelgreenacre/CODAinPractice. The R package easyCODA, which accompanies this book, is available on CRAN -- note that you should have version 0.25 or higher. The latest version of the package will always be available on R-Forge and can be installed from R with this instruction: install.packages("easyCODA", repos="http://R-Forge.R-project.org").