This classic text on multiple regression is noted for its nonmathematical, applied, and data-analytic approach. Readers profit from its verbal-conceptual exposition and frequent use of examples. The applied emphasis provides clear illustrations of the principles and provides worked examples of the types of applications that are possible. Researchers learn how to specify regression models that directly address their research questions. An overview of the fundamental ideas of multiple regression and a review of bivariate correlation and regression and other elementary statistical concepts provide a strong foundation for understanding the rest of the text. The third edition features an increased emphasis on graphics and the use of confidence intervals and effect size measures, and an accompanying CD with data for most of the numerical examples along with the computer code for SPSS, SAS, and SYSTAT. Applied Multiple Regression serves as both a textbook for graduate students and as a reference tool for researchers in psychology, education, health sciences, communications, business, sociology, political science, anthropology, and economics. An introductory knowledge of statistics is required. Self-standing chapters minimize the need for researchers to refer to previous chapters.
This classic text on multiple regression is noted for its nonmathematical, applied, and data-analytic approach. Readers profit from its verbal-conceptual exposition and frequent use of examples. The applied emphasis provides clear illustrations of the principles and provides worked examples of the types of applications that are possible. Researchers learn how to specify regression models that directly address their research questions. An overview of the fundamental ideas of multiple regression and a review of bivariate correlation and regression and other elementary statistical concepts provide a strong foundation for understanding the rest of the text. The third edition features an increased emphasis on graphics and the use of confidence intervals and effect size measures, and an accompanying website with data for most of the numerical examples along with the computer code for SPSS, SAS, and SYSTAT, at www.psypress.com/9780805822236 . Applied Multiple Regression serves as both a textbook for graduate students and as a reference tool for researchers in psychology, education, health sciences, communications, business, sociology, political science, anthropology, and economics. An introductory knowledge of statistics is required. Self-standing chapters minimize the need for researchers to refer to previous chapters.
Warum soll man sich in der Psychologie mit Forschungsmethoden auseinandersetzen? Wie können Hypothesen für empirische Untersuchungen gewonnen werden? Wie kann man psychische Phänomene messen? Warum werden in der Psychologie Experimente durchgeführt? Das Buch liefert Antworten auf diese und viele andere Fragen und führt in verständlicher, übersichtlicher Form in die Forschungsmethoden der Psychologie ein. Leserinnen und Leser erfahren, wie empirische Studien in der Psychologie ablaufen, mit welchen Methoden Daten erhoben und ausgewertet werden können und was es bei der Ergebnispräsentation zu beachten gilt. Zahlreiche Beispiele veranschaulichen den Stoff und machen deutlich, wie wichtig gute Methodenkenntnisse sind.
Rebecca M. Warner's Applied Statistics: From Bivariate Through Multivariate Techniques, Second Edition provides a clear introduction to widely used topics in bivariate and multivariate statistics, including multiple regression, discriminant analysis, MANOVA, factor analysis, and binary logistic regression. The approach is applied and does not require formal mathematics; equations are accompanied by verbal explanations. Students are asked to think about the meaning of equations. Each chapter presents a complete empirical research example to illustrate the application of a specific method. Although SPSS examples are used throughout the book, the conceptual material will be helpful for users of different programs. Each chapter has a glossary and comprehension questions.
A comprehensive, easy-to-understand guide to the entire research process, this book quickly and efficiently equips advanced students and research assistants to conduct a full-scale investigation. The book is organized around the idea of a 'research script' that is, it follows the standard mode of research planning and design, data collection and analysis, and results writing. The volume contains 35 chapters, some co-authored by advanced graduate students who give their fellow students a touch of the 'real world' adding to the clarity and practicality of many chapters.
Click on the Supplements tab above for further details on the different versions of SPSS programs. The canonical Handbook is completely updated with more student-friendly features The Handbook of Social Work Research Methods is a cutting-edge volume that covers all the major topics that are relevant for Social Work Research methods. Edited by Bruce Thyer and containing contributions by leading authorities, this Handbook covers both qualitative and quantitative approaches as well as a section that delves into more general issues such as evidence based practice, ethics, gender, ethnicity, International Issues, integrating both approaches, and applying for grants. New to this Edition More content on qualitative methods and mixed methods More coverage of evidence-based practice More support to help students effectively use the Internet A companion Web site at www.sagepub.com/thyerhdbk2e containing a test bank and PowerPoint slides for instructors and relevant SAGE journal articles for students. This Handbook serves as a primary text in the methods courses in MSW programs and doctoral level programs. It can also be used as a reference and research design tool for anyone doing scholarly research in social work or human services.
Ein Lehrbuch mit 49 Beiträgen namhafter klinischer Psychologen – gegliedert in die Grundlagen der klinischen Psychologie, in Basiskurse zu psychotherapeutischen Verfahren und Vertiefungskurse zu allen wichtigen Störungsbildern und Anwendungsfeldern. Für die 2. Auflage wurden zahlreiche Kapitel überarbeitet und neue Kapitel zu psychischen Störungen im Kindesalter, pathologischem Glücksspiel und bipolaren Störungen ergänzt. Eine Begleitwebsite enthält interaktive Lerntools für Studierende und Lehrmaterialien für Dozenten.
Psychology is of interest to academics from many fields, as well as to the thousands of academic and clinical psychologists and general public who can't help but be interested in learning more about why humans think and behave as they do. This award-winning twelve-volume reference covers every aspect of the ever-fascinating discipline of psychology and represents the most current knowledge in the field. This ten-year revision now covers discoveries based in neuroscience, clinical psychology's new interest in evidence-based practice and mindfulness, and new findings in social, developmental, and forensic psychology.
The complexity of social problems necessitates that social work researchers understand and apply multivariate statistical methods in their investigations. In this pocket guide, the authors introduce readers to three of the more frequently used multivariate methods in social work research with an emphasis on basic statistics. The primary aim is to prepare entry-level doctoral students and early career social work researchers in the use of multivariate methods by providing an easy-to-understand presentation, building on the basic statistics that inform them. The pocket guide begins with a review of basic statistics, hypothesis testing with inferential statistics, and bivariate analytic methods. Subsequent sections describe bivariate and multiple linear regression analyses, one-way and two-way analysis of variance (ANOVA) and covariance (ANCOVA), and path analysis. In each chapter, the authors introduce the various basic statistical procedures by providing definitions, formulas, descriptions of the underlying logic and assumptions of each procedure, and examples of how they have been used in social work research literature, particularly with diverse populations. They also explain estimation procedures and how to interpret results. The multivariate chapters conclude with brief step-by-step instructions for conducting multiple regression analysis and one-way ANOVA in Statistical Package for the Social Sciences (SPSS), and path analysis in Amos, using data from the National Educational Longitudinal Study of 1988 (NELS: 88). As an additional supplement, the book offers a companion website that provides more detailed instructions, as well as data sets and worked examples.
Genetic Counseling Research: A Practical Guide is the first text devoted to research methodology in genetic counseling. This text offers step-by-step guidance for conducting research, from the development of a question to the publication of findings. Genetic counseling examples, user-friendly worksheets, and practical tips guide readers through the research and publication processes. With a highly accessible, pedagogical approach, this book will help promote quality research by genetic counselors and research supervisors--and in turn, increase the knowledge base for genetic counseling practice, other aspects of genetic counseling service delivery, and professional education. It will be an invaluable resource to the next generation of genetic counseling and its surrounding disciplines.
Psychologists, researchers, teachers, and students need complete and comprehensive information in the fields of psychology and behavioral science. The Corsini Encyclopedia of Psychology, Volume Three has been the reference of choice for almost three decades. This indispensable resource is updated and expanded to include much new material. It uniquely and effectively blends psychology and behavioral science. The Fourth Edition features over 1,200 entries; complete coverage of DSM disorders; and a bibliography of over 10,000 citations. Readers will benefit from up-to-date and authoritative coverage of every major area of psychology.
The Essence of Multivariate Thinking is intended to make multivariate statistics more accessible to a wide audience. To encourage a more thorough understanding of multivariate methods, author Lisa Harlow suggests basic themes that run through most statistical methodology. The most pervasive theme is multiplicity. The author argues that the use of multivariate methods encourages multiple ways of investigating phenomena. She explains that widening our lens to identify multiple theories, constructs, measures, samples, methods, and time points provide greater reliability and validity in our research. Dr. Harlow then shows how these themes are applied to several multivariate methods, with the hope that this will ease understanding in the basic concepts of multivariate thinking. Formulas are kept at a minimum. The first three chapters review the core themes that run through multivariate methods. Seven different multivariate methods are then described using 10 questions that illuminate the main features, uses, multiplicity, themes, interpretations, and applications. The seven methods covered are multiple regression, analysis of covariance, multivariate analysis of variance, discriminant function analysis, logistic regression, canonical correlation, and principal components/factor analysis. The final chapter pulls together the principal themes and features charts that list common themes and how they pertain to each of the methods discussed. The Essence of Multivariate Thinking, features: A unique focus on the underlying themes that run through most multivariate methods. A dual focus on significance tests and effect sizes to encourage readers to adopt a thorough approach to assessing the significance and magnitude of their findings. A detailed example for each method to delineate how the multivariate themes apply. Tabular results from statistical analysis programs that mirror sections of the output files. A common dataset throughout the chapters to provide continuity with the variables and research questions. A CD with data, SAS program setup and output, homework exercises, and chapter lectures. This book is useful to advanced students, professionals, and researchers interested in applying multivariate methods in such fields as behavioral medicine, social, health, personality, developmental, cognitive, and industrial-organizational psychology, as well as in education and evaluation. A preliminary knowledge of basic statistics, research methods, basic algebra, and finite mathematics is recommended.
The contributors to Best Practices in Quantitative Methods envision quantitative methods in the 21st century, identify the best practices, and, where possible, demonstrate the superiority of their recommendations empirically. Editor Jason W. Osborne designed this book with the goal of providing readers with the most effective, evidence-based, modern quantitative methods and quantitative data analysis across the social and behavioral sciences. The text is divided into five main sections covering select best practices in Measurement, Research Design, Basics of Data Analysis, Quantitative Methods, and Advanced Quantitative Methods. Each chapter contains a current and expansive review of the literature, a case for best practices in terms of method, outcomes, inferences, etc., and broad-ranging examples along with any empirical evidence to show why certain techniques are better. Key Features: Describes important implicit knowledge to readers: The chapters in this volume explain the important details of seemingly mundane aspects of quantitative research, making them accessible to readers and demonstrating why it is important to pay attention to these details. Compares and contrasts analytic techniques: The book examines instances where there are multiple options for doing things, and make recommendations as to what is the "best" choice—or choices, as what is best often depends on the circumstances. Offers new procedures to update and explicate traditional techniques: The featured scholars present and explain new options for data analysis, discussing the advantages and disadvantages of the new procedures in depth, describing how to perform them, and demonstrating their use. Intended Audience: Representing the vanguard of research methods for the 21st century, this book is an invaluable resource for graduate students and researchers who want a comprehensive, authoritative resource for practical and sound advice from leading experts in quantitative methods.
Vital Statistics: an introduction to health science statistics e-book is a new Australian publication. This textbook draws on real world, health-related and local examples, with a broad appeal to the Health Sciences student. It demonstrates how an understanding of statistics is useful in the real world, as well as in statistics exams. Vital Statistics: an introduction to health science statistics e-book is a relatively easy-to-read book that will painlessly introduce or re-introduce you to the statistical basics before guiding you through more demanding statistical challenges. Written in recognition of Health Sciences courses which require knowledge of statistical literacy, this book guides the reader to an understanding of why, as well as how and when to use statistics. It explores: How data relates to information, and how information relates to knowledge How to use statistics to distinguish information from disinformation The importance of probability, in statistics and in life That inferential statistics allow us to infer from samples to populations, and how useful such inferences can be How to appropriately apply and interpret statistical measures of difference and association How qualitative and quantitative methods differ, and when it’s appropriate to use each The special statistical needs of the health sciences, and some especially health science relevant statistics The vital importance of computers in the statistical analysis of data, and gives an overview of the most commonly used analyses Real-life local examples of health statistics are presented, e.g. A study conducted at the Department of Obstetrics and Gynecology, University of Utah School of Medicine, explored whether there might be a systematic bias affecting the results of genetic specimen tests, which could affect their generalizability. Reader-friendly writing style t-tests/ ANOVA family of inferential statistics all use variants of the same basic formula Learning Objectives at the start of each chapter and Quick Reference Summaries at the end of each chapter provide the reader with a scope of the content within each chapter.
This volume reviews the challenges and alternative approaches to modeling how individuals change across time and provides methodologies and data analytic strategies for behavioral and social science researchers. This accessible guide provides concrete, clear examples of how contextual factors can be included in most research studies. Each chapter can be understood independently, allowing readers to first focus on areas most relevant to their work. The opening chapter demonstrates the various ways contextual factors are represented—as covariates, predictors, outcomes, moderators, mediators, or mediated effects. Succeeding chapters review "best practice" techniques for treating missing data, making model comparisons, and scaling across developmental age ranges. Other chapters focus on specific statistical techniques such as multilevel modeling and multiple-group and multilevel SEM, and how to incorporate tests of mediation, moderation, and moderated mediation. Critical measurement and theoretical issues are discussed, particularly how age can be represented and the ways in which context can be conceptualized. The final chapter provides a compelling call to include contextual factors in theorizing and research. This book will appeal to researchers and advanced students conducting developmental, social, clinical, or educational research, as well as those in related areas such as psychology and linguistics.
The Wiley-Blackwell Handbook of Individual Differences provides a comprehensive, up-to-date overview of recent research, current perspectives, practical applications, and likely future developments in individual differences. Brings together the work of the top global researchers within the area of individual differences, including Philip L. Ackerman, Ian J. Deary, Ed Diener, Robert Hogan, Deniz S. Ones and Dean Keith Simonton Covers methodological, theoretical and paradigm changes in the area of individual differences Individual chapters cover core areas of individual differences including personality and intelligence, biological causes of individual differences, and creativity and emotional intelligence
Decades of research indicate the important connections among academic motivation and achievement, social relationships, and school culture. However, much of this research has been conducted in homogenous American schools serving middle class, average achieving, Anglo-student populations. This edited volume will argue that school culture is a reflection of the society in which the school is embedded and comprises various aspects, including individualism, competition, cultural stereotypes, and extrinsically guided values and rewards. They address three specific conceptual questions: How do differences in academic motivation for diverse groups of students change over time? How do students' social cognitions influence their motivational processes and outcomes in school? And what has been done to enhance academic motivation? To answer this last question, the contributors describe empirically validated intervention programs for improving academic motivation in students from elementary school through college.
The updated Second Edition of Alan C. Elliott and Wayne A. Woodward’s “cut to the chase” IBM SPSS guide quickly explains the when, where, and how of statistical data analysis as it is used for real-world decision making in a wide variety of disciplines. This one-stop reference provides succinct guidelines for performing an analysis using SPSS software, avoiding pitfalls, interpreting results, and reporting outcomes. Written from a practical perspective, IBM SPSS by Example, Second Edition provides a wealth of information—from assumptions and design to computation, interpretation, and presentation of results—to help users save time, money, and frustration.
Designed to advance knowledge about violence against women and to serve as an inspiration to those studying or working in the field, this companion reader's 20 original articles focus first on theoretical and methodological issues, then on types of violence against women, and finally on prevention and direct intervention. Readers will find a wide range of articles that draw attention to the global dimensions of violence against women and the importance of taking into account political, economic, and cultural differences across diverse groups of people. While the book's articles are designed as companion pieces to the chapters in the Second Edition of the Sourcebook, this reader may also be used as a stand-alone text by those researching specific topics, such as diversity issues, conducting trainings, or teaching advanced courses, such as international social work.
Understanding Girls' Problem Behavior presents an overview of recent studies by leading researchers into key aspects of the development of problem behavior in girls. Integrates interdisciplinary research into girls’ problem behaviors (e.g. aggression, antisocial behavior, rule breaking) Unique in seeking to understand girls’ problem behaviors in their own right Follows the maturing girl from adolescence to adulthood, concluding at the point where she herself becomes a parent and forms new relationships Gives attention to the critical contexts of problem behavior development—society and neighborhood, as well as family and peer contexts