This second edition presents the core fundamentals of the subject in 11 manageable chapters while maintaining the book's scientific integrity. The research methods students need to understand, interpret, and analyze social psychological research are emphasized throughout. The streamlined approach provides an economical textbook for students and a flexible format that allows instructors to cover the entire book in a single semester. A book specific Web site contains a free online study guide and a variety of teaching tools. An Instructor's Manual/Test Bank and a Computerized Test Bank are also available.

Do you want to spend less time studying but end up with better grades, and a deeper understanding of the subject? Studying psychology is a skill that can be learned. In this unique and practical 'how to' guide, Warren Davies offers some simple techniques that will enable students to retain information, organise their workload, and be more productive. By applying some simple and easy-to-make changes to your study habits, you will learn how to: Get more work done in less time Use memory techniques to help you breeze through exams Beat procrastination Develop a deep grasp of difficult topics Write excellent essays (including how to avoid the seven most common essay errors) Cut your study time in half Understand the 'results' section of research papers Write a dissertation to publishable standard. This book is written specifically with psychology undergraduate students in mind, and as such will enhance your learning and improve your grades with techniques that actually work.

A greatly expanded and heavily revised second edition, this popular guide provides instructions and clear examples for running analyses of variance (ANOVA) and several other related statistical tests of significance with SPSS. No other guide offers the program statements required for the more advanced tests in analysis of variance. All of the programs in the book can be run using any version of SPSS, including versions 11 and 11.5. A table at the end of the preface indicates where each type of analysis (e.g., simple comparisons) can be found for each type of design (e.g., mixed two-factor design). Providing comprehensive coverage of the basic and advanced topics in ANOVA, this is the only book available that provides extensive coverage of SPSS syntax, including the commands and subcommands that tell SPSS what to do, as well as the pull-down menu point-and-click method (PAC). Detailed explanation of the syntax, including what is necessary, desired, and optional helps ensure that users can validate the analysis being performed. The book features the output of each design along with a complete explanation of the related printout. The new edition was reorganized to provide all analysis related to one design type in the same chapter. It now features expanded coverage of analysis of covariance (ANCOVA) and mixed designs, new chapters on designs with random factors, multivariate designs, syntax used in PAC, and all new examples of output with complete explanations. The new edition is accompanied by downloadable resources with all of the book's data sets, as well as exercises for each chapter. This book is ideal for readers familiar with the basic concepts of the ANOVA technique including both practicing researchers and data analysts, as well as advanced students learning analysis of variance.

The rising reliance on testing in American education and for licensure and certification has been accompanied by an escalation in cheating on tests at all levels. Edited by two of the foremost experts on the subject, the Handbook of Quantitative Methods for Detecting Cheating on Tests offers a comprehensive compendium of increasingly sophisticated data forensics used to investigate whether or not cheating has occurred. Written for practitioners, testing professionals, and scholars in testing, measurement, and assessment, this volume builds on the claim that statistical evidence often requires less of an inferential leap to conclude that cheating has taken place than do other, more common sources of evidence. This handbook is organized into sections that roughly correspond to the kinds of threats to fair testing represented by different forms of cheating. In Section I, the editors outline the fundamentals and significance of cheating, and they introduce the common datasets to which chapter authors' cheating detection methods were applied. Contributors describe, in Section II, methods for identifying cheating in terms of improbable similarity in test responses, preknowledge and compromised test content, and test tampering. Chapters in Section III concentrate on policy and practical implications of using quantitative detection methods. Synthesis across methodological chapters as well as an overall summary, conclusions, and next steps for the field are the key aspects of the final section.

Developed specifically for students in the behavioral and brain sciences, this is the only textbook that provides an accessible and practical overview of the range of human neuroimaging techniques. Methods covered include functional and structural magnetic resonance imaging, positron emission tomography, electroencephalography, magnetoencephalography, multimodal imaging, and various brain stimulation methods. Experimental design, image processing, and statistical inference are also addressed, with chapters for both basic and more advanced data analyses. Key concepts are illustrated through research studies on the relationship between brain and behavior, and practice questions are included throughout to test knowledge and aid self-study. Offering just the right amount of detail for understanding how major imaging techniques can be applied to answer neuroscientific questions, and the practical skills needed for future research, this is an essential text for advanced undergraduate and graduate students in psychology, neuroscience, and cognitive science programs taking introductory courses on human neuroimaging.

This book presents the reader with a set of diverse, carefully developed and clearly specified systems of transcription and coding, arising from contrasting theoretical perspectives, and presented as alternative choices, situated within the theoretical domain most natural to each. The perspectives represented include first and second language acquisition, interethnic and crosscultural interaction, information structure, and the study of discourse influences on linguistic expression. In the contributed chapters, the designers of these systems provide a distillation of collective experiences from the past quarter century, telling in their own words their perspectives on language processes, how these perspectives have shaped their choice of methodology in transcription and coding of natural language, and describing their systems in detail. Overview chapters by the editors then provide design principles and guidelines concerning issues pertinent to all systems, including such things as reliability, validity, ease of learning, computational tractability, and robustness against error. The final chapter is a compendium of existing computerized archives of language data and information sources together with details concerning data access and use.

These two companion volumes provide a comprehensive review and critical evaluation of the major DSM-III and DSM-III-R child disorders. Their major goal is to provide diagnostic and assessment guidelines that are based on scientific literature in specific clinical domains. Each chapter contains a discussion of the historical background of a particular diagnosis, definitional issues, a critical but selective review of the literature addressing the diagnosis in question, proposed changes in the diagnostic criteria based on the available literature, and proposed assessment models and methods based on the designated criteria. Given the scientific bases for many of these discussions of diagnostic criteria, these two volumes will serve professionals and graduate students in a wide variety of fields: clinical child psychology, child psychiatry, pediatrics, pediatric and school psychology, special education, social work, and other child mental health specialties.

"This is a great overview of the field of model-based clustering and classification by one of its leading developers. McNicholas provides a resource that I am certain will be used by researchers in statistics and related disciplines for quite some time. The discussion of mixtures with heavy tails and asymmetric distributions will place this text as the authoritative, modern reference in the mixture modeling literature." (Douglas Steinley, University of Missouri) Mixture Model-Based Classification is the first monograph devoted to mixture model-based approaches to clustering and classification. This is both a book for established researchers and newcomers to the field. A history of mixture models as a tool for classification is provided and Gaussian mixtures are considered extensively, including mixtures of factor analyzers and other approaches for high-dimensional data. Non-Gaussian mixtures are considered, from mixtures with components that parameterize skewness and/or concentration, right up to mixtures of multiple scaled distributions. Several other important topics are considered, including mixture approaches for clustering and classification of longitudinal data as well as discussion about how to define a cluster Paul D. McNicholas is the Canada Research Chair in Computational Statistics at McMaster University, where he is a Professor in the Department of Mathematics and Statistics. His research focuses on the use of mixture model-based approaches for classification, with particular attention to clustering applications, and he has published extensively within the field. He is an associate editor for several journals and has served as a guest editor for a number of special issues on mixture models.

Occupational health psychology (OHP) involves the application of psychology to improving the quality of work life and to promoting and protecting the safety, health and well-being of employees. Achieving these aims requires researchers and practitioners to possess in-depth knowledge of the processes that are presumed to bring about the desired outcomes. To date, most studies in OHP have relied on cross-sectional designs in examining these processes. In such designs all variables of interest are measured simultaneously. Although this has generated useful insights in how particular phenomena are associated, such designs cannot be trusted when it comes to drawing causal inferences: association is not causation. This book therefore focuses on longitudinal research designs in OHP, whereby the concepts of interest are measured several times, offering much stronger evidence for causal relationships. The authors focus on design issues in longitudinal research (such as the number of measurements chosen, and the length of the time lags between these measurements), and illustrate these issues in the context of applied research on topics such as the work-family interface, conflict at work, and employee well-being. By doing so this volume provides a state-of-the-art overview of current research in OHP, both in terms of its findings and methodologies. This book is based on a special issue of the journal Work & Stress.

Practical Research with Children is designed to help the reader understand techniques for research with children, based on real world experience. The book describes a wide range of research methods, focusing equally on quantitative and qualitative approaches, and considers how different methods can be integrated. It highlights the benefits and challenges of each method and gives emphasis to best practice, with expert guidance on how to avoid potential pitfalls in order to obtain valuable insights into how children develop. The volume includes fifteen chapters arranged over three sections. Each chapter explores a particular method, or combination of methods, and discusses both theoretical and practical issues, using a diversity of domains, including different ages, cultures, populations and settings. Uniquely, the book includes newer methods (such as eye tracking and digital technologies) alongside well-established behavioural methods which are used for research with children. With contributions from internationally renowned researchers and practitioners from a range of disciplines, the book will be indispensable reading for a wide audience, including for students in psychology, education and nursing undertaking research projects with children, and also for anyone looking to understand the research behind current theories in child development.

Originally published in 1992, the editors of this volume fulfill three main goals: to take stock of progress in the development of data-analysis procedures for single-subject research; to clearly explain errors of application and consider them within the context of new theoretical and empirical information of the time; and to closely examine new developments in the analysis of data from single-subject or small n experiments. To meet these goals, this book provides examples of applicable single-subject research data analysis. It presents a wide variety of topics and perspectives and hopes that readers will select the data-analysis strategies that best reflect their methodological approaches, statistical sophistication, and philosophical beliefs. These strategies include visual analysis, nonparametric tests, time-series experiments, applications of statistical procedures for multiple behaviors, applications of meta-analysis in single-subject research, and discussions of issues related to the application and misapplication of selected techniques.

Provides researchers with a reproducible research workflow for using R/RStudio to make the entire researchprocess reproducible; from data gathering, to analysis, to presentation Includes instructions not only for creating reproducible research in R, but also extensively discusses how to take advantage of recent developments in RStudio. Emphasizes the presentation of reproducible research with non-print formats such as HTML5 slideshows, blogs, and other web-based content. Covers a range of techniques to organize and remotely store files at all stages of the research process. These techniques both streamline the research process, especially by making revisions easier, and enhance The book itself will be reproducible, as all of the data, analysis, and markup files will be made available online.

The heart of this book is the translation of The Life Space of the Urban Child, written in 1935 by Martha and Hans Heinrich Muchow. Life Space provides a fresh look at children as actors and how they absorb their city environments. It uses an empirical base connected with theories about the worlds in which children live. The first section provides historical background on Muchow's study and the author. The second section presents the translation of the Life Space study, as well as comments from an environmental psychologist's perspective. The third section reviews the study's theoretical foundations, including the concept of "critical personalism," the perspectives of phenomenology, and the notion of Umwelt (environment). The last section addresses various lines of research developed from the Life Space study, including Muchow's work in describing children in urban environments, methodological approaches, and the significance of space in social science and educational contexts. The manner in which Martha Muchow conducted her studies is itself of note. She obtained access to the children in their environments and combined observation with cartographies and essays produced by the children. This approach was new at the time and continues to inspire researchers today. This volume is the latest work in Transaction's History and Theory of Psychology series.

Research Methods is an introduction to the importance of scientific research in everyday life and uses familiar examples to keep students engaged. The text analyzes controversies in psychology to stimulate student interest while explaining crucial methodological concepts. It presents ethical issues related to research, as well as social and cultural factors that might affect it, and provides a comprehensive introduction to a wide variety of methodologies. Through this book, students will learn how to generate research questions and select appropriate methodology, as well as to write a successful research report.

* It is a straightforward, conversational introduction to statistics that delivers exactly what its title promises. * Each chapter begins with a brief overview of a statistic that describes what the statistic does and when to use it, followed by a detailed step-by-step explanation of how the statistic works and exactly what information it provides. * Chapters also include an example of the statistic (or statistics) in use in real-world research, "Worked Examples," "Writing It Up" sections that demonstrate how to write about each statistic, "Wrapping Up and Looking Forward" sections, and practice work problems. * A new chapter on person-centered analyses, including cluster analysis and latent class analysis (LCA) has been added (Chapter 16). * Person-centered analysis is an important alternative to the more commonly used variable-centered analyses (e.g., t tests, ANOVA, regression) and is gaining popularity in social-science research. * The chapter on non-parametric statistics (Chapter 14) was enhanced significantly with in-depth descriptions of Mann-Whitney U, Kruskall-Wallace, and Wilcoxon Signed-Rank analyses. * These non-parametric statistics are important alternatives to statistics that rely on normally distributed data. * This new edition also includes more information about the assumptions of various statistics, including a detailed explanation of the assumptions and consequences of violating the assumptions of regression (Chapter 13). * There is more information provided about the importance of the normal distribution in statistics (Chapters 4 and 7). * Each of the last nine chapters includes an example from the real world of research that employs the statistic, or statistics, covered in the chapter. * Altogether, these improvements provide important foundational information about how inferential statistics work and additional statistical tools that are commonly used by researchers in the social sciences. * The text works as a standalone or as a supplement and covers a range of statistical concepts from descriptive statistics to factor analysis and person-centered analyses.

The distinguishing feature of experimental psychology is not so much the nature of its theories as the methods used to test their validity. The first edition of Experimental Design and Statistics provided a clear and lucid introduction to these methods and the statistical techniques which support them. For this new edition the text has been revised, the coverage of two-sample tests has been extended, and new sections have been added introducing one-sample tests, linear regression and the product-moment correlation coefficient. Problems associated with the applications of experimental design and how to use observations of behaviour in research are key questions for all introductory students of psychology. This new and expanded edition provides them with an invaluable text and source.

Want to master research methods in psychology? Look no further! Written with new students in mind, this book will help you understand and apply research methods to every part of your degree. It will help you develop your critical and analytical skills by making features of key issues such as ethics and cultural context. It aims to entertain with interesting facts, and will enhance your understanding with examples of real studies. Other features include: Skoolkid errors Ig Nobel Prize Whoa there! and are all designed to make the study of methods enjoyable and easy.

First Published in 1987. Routledge is an imprint of Taylor & Francis, an informa company.

The topic of ego development developed when psychoanalysis did not fulfill all the initial hopes during its early period of prominence. Clinicians--psychiatrists, psychologists, social workers, and counselors--realized that they needed to know more than their patients' or clients' psychopathology or normalcy and their psychosexual behavior and drives. The method for scoring sentence completions presented in this manual was originally developed for a study of women and adolescent girls. By the time it was first published in 1970, however, the method had already come into use in studies of men and boys. Since then, it has been used with widely varying samples, and the test has been translated into several other languages. This wide adoption testifies to the need for such a test. The present version of the manual incorporates three major improvements: * it is based on data from, and is intended for use with, both males and females, * its format is easier to use, and * the examples cited reflect current public attitudes. The format of the scoring manual for the Sentence Completion Test (SCT) is radically changed from the original, making it easier to find the correct rating for a response. The rating scale itself is kept simple and the basic concept of ego development is the same. A tutorial is included to assist in calculating the Total Protocol Ratings (TPRs). ALTERNATIVE BLURB!!! The Washington University Sentence Completion Test, which was developed by Jane Loevinger, is a free-response, semi-projective instrument for the assessment of ego development. The first manual for administering and scoring the test was published in 1970. In addition to its widespread use in the United States, it has also been adopted for use in Canada, the United Kingdom, France, Germany, Italy, the Netherlands, Japan, India, and South Africa. The WUSCT has been used for research in the fields of adolescent personality development, moral development, infancy and parenting, family and gender studies, multiculturalism, religion, psychopathology and psychotherapy, vocational studies, and social and organizational psychology. It is most frequently used by researchers and practitioners in psychology, counseling, social work, and education. This book represents a revised edition of the WUSCT scoring manual, including all items in the 1981 forms, which were revised for use with both men and women. The content reflects current social attitudes, which have changed on some topics since the publication of the original 1970 manual. Although there have been minor changes in terminology, the conception of ego development is unchanged, and the stages of the construct are essentially the same. The format of the scoring manual, however, has been radically changed for ease of use in rating responses. (The rating scale itself, which is the same for all items, is kept simple.) A tutorial is included to assist in calculating the Total Protocol Ratings.

Power Analysis of Trials with Multilevel Data covers using power and sample size calculations to design trials that involve nested data structures. The book gives a thorough overview of power analysis that details terminology and notation, outlines key concepts of statistical power and power analysis, and explains why they are necessary in trial design. It guides you in performing power calculations with hierarchical data, which enables more effective trial design. The authors are leading experts in the field who recognize that power analysis has attracted attention from applied statisticians in social, behavioral, medical, and health science. Their book supplies formulae that allow statisticians and researchers in these fields to perform calculations that enable them to plan cost-efficient trials. The formulae can also be applied to other sciences. Using power analysis in trial design is increasingly important in a scientific community where experimentation is often expensive, competition for funding among researchers is intense, and agencies that finance research require proposals to give thorough justification for funding. This handbook shows how power analysis shapes trial designs that have high statistical power and low cost, using real-life examples. The book covers multiple types of trials, including cluster randomized trials, multisite trials, individually randomized group treatment trials, and longitudinal intervention studies. It also offers insight on choosing which trial is best suited to a given project. Power Analysis of Trials with Multilevel Data helps you craft an optimal research design and anticipate the necessary sample size of data to collect to give your research maximum effectiveness and efficiency.

A Sound Basis for the Theory of Statistical Inference Measuring Statistical Evidence Using Relative Belief provides an overview of recent work on developing a theory of statistical inference based on measuring statistical evidence. It shows that being explicit about how to measure statistical evidence allows you to answer the basic question of when a statistical analysis is correct. The book attempts to establish a gold standard for how a statistical analysis should proceed. It first introduces basic features of the overall approach, such as the roles of subjectivity, objectivity, infinity, and utility in statistical analyses. It next discusses the meaning of probability and the various positions taken on probability. The author then focuses on the definition of statistical evidence and how it should be measured. He presents a method for measuring statistical evidence and develops a theory of inference based on this method. He also discusses how statisticians should choose the ingredients for a statistical problem and how these choices are to be checked for their relevance in an application.

This is the first practitioner-oriented guide to basic psychometrics--the science behind test construction and validation. It is an essential course text and clinical reference for anyone who needs to select and administer diagnostic tests or review test score data obtained by others. Without assuming any mathematical background, the author describes the fundamentals of diagnostic testing, how to interpret score data, and how specific tests are used in school psychology, special education, counseling, and other contexts. Concepts such as reliability, validity, and fairness and test bias are explained in an accessible, conversational way. Detailed case examples illustrate the dos and don'ts of presenting test score data to clients, parents, and teachers in oral feedback and written reports. Pedagogical Features: *End-of-chapter exercises that emphasize application and understanding, with answers at the end of the book. *Key terms are bolded throughout and accessibly explained in the end-of-book glossary. *Resource appendix--annotated guide to articles and books on more advanced topics in psychometrics, assessment, and testing.

This book begins with an introductory outline of the structure of the city politics of the United States. There is a study of the city in the federal system, including the politics of feudal aid. This is followed by four case studies: the political roles of mayor, manager, boss and adminstrator-entrepreneur in the city.

Madgwick concludes with some comparative reflections indicating the significance of this study for British local government.

This book was first published in 1970.

Winner of the 2015 Sugiyama Meiko Award (Publication Award) of the Behaviormetric Society of Japan Developed by the authors, generalized structured component analysis is an alternative to two longstanding approaches to structural equation modeling: covariance structure analysis and partial least squares path modeling. Generalized structured component analysis allows researchers to evaluate the adequacy of a model as a whole, compare a model to alternative specifications, and conduct complex analyses in a straightforward manner. Generalized Structured Component Analysis: A Component-Based Approach to Structural Equation Modeling provides a detailed account of this novel statistical methodology and its various extensions. The authors present the theoretical underpinnings of generalized structured component analysis and demonstrate how it can be applied to various empirical examples. The book enables quantitative methodologists, applied researchers, and practitioners to grasp the basic concepts behind this new approach and apply it to their own research. The book emphasizes conceptual discussions throughout while relegating more technical intricacies to the chapter appendices. Most chapters compare generalized structured component analysis to partial least squares path modeling to show how the two component-based approaches differ when addressing an identical issue. The authors also offer a free, online software program (GeSCA) and an Excel-based software program (XLSTAT) for implementing the basic features of generalized structured component analysis.

Originally published in 1992, the editors of this volume fulfill three main goals: to take stock of progress in the development of data-analysis procedures for single-subject research; to clearly explain errors of application and consider them within the context of new theoretical and empirical information of the time; and to closely examine new developments in the analysis of data from single-subject or small n experiments. To meet these goals, this book provides examples of applicable single-subject research data analysis. It presents a wide variety of topics and perspectives and hopes that readers will select the data-analysis strategies that best reflect their methodological approaches, statistical sophistication, and philosophical beliefs. These strategies include visual analysis, nonparametric tests, time-series experiments, applications of statistical procedures for multiple behaviors, applications of meta-analysis in single-subject research, and discussions of issues related to the application and misapplication of selected techniques.