This book is a step-by-step guide for instructors on how to teach a psychology research methods course at the undergraduate or graduate level. It provides various approaches for teaching the course including lecture topics, difficult concepts for students, sample labs, test questions, syllabus guides and policies, as well as a detailed description of the requirements for the final experimental paper. This book is also supplemented with anecdotes from the author's years of experience teaching research methods classes. Chapters in this book include information on how to deliver more effective lectures, issues you may encounter with students, examples of weekly labs, tips for teaching research methods online, and much more. This book is targeted towards the undergraduate or graduate professor who has either not yet taught research methods or who wants to improve his or her course. Using step by step directions, any teacher will be able to follow the guidelines found in this book that will help them succeed.How to Teach a Course in Research Methods for Psychology Students is a valuable resource for anyone teaching a quantitative research methods course at the college or university level.

Contemporary research on major emotional disorders emphasizes their commonalities rather than their differences. This research continues to lend support for a unified transdiagnostic approach to treatment of these disorders that considers their commonalities and is applicable to a range of emotional problems. Unified Protocol for Transdiagnostic Treatment of Emotional Disorders provides an alternative to disorder-specific treatments of various emotional disorders, designed to be applicable to the wide range of anxiety and other disorders with strong emotional components. The Therapist Guide and accompanying client Workbook present an eight-module therapy program that puts substantial emphasis on emotion-focused approaches, helping clients confront and experience challenging emotions while teaching them how to regulate those emotions. Expanded considerably in this second edition, the volume provides guidance on using the Unified Protocol (UP) to address problems not only with anxiety, but also with depression, eating disorders, non-suicidal self-injury, substance use, and anger. Treatment procedures have been further elucidated and more guidance is provided to practitioners on how to present key treatment concepts. Chapters brand new to this updated edition introduce functional assessment and describe how to provide the UP in a group format, while patient materials have been revised, streamlined, and made more user-friendly.

The field of mathematical psychology began in the 1950s and includes both psychological theorizing, in which mathematics plays a key role, and applied mathematics, motivated by substantive problems in psychology. Central to its success was the publication of the first Handbook of Mathematical Psychology in the 1960s. The psychological sciences have since expanded to include new areas of research, and significant advances have been made in both traditional psychological domains and in the applications of the computational sciences to psychology. Upholding the rigor of the first title in this field to be published, the New Handbook of Mathematical Psychology reflects the current state of the field by exploring the mathematical and computational foundations of new developments over the last half-century. This first volume focuses on select mathematical ideas, theories, and modeling approaches to form a foundational treatment of mathematical psychology.

This text is about doing science and the active process of reading, learning, thinking, generating ideas, designing experiments, and the logistics surrounding each step of the research process. In easy-to-read, conversational language, Kim MacLin teaches students experimental design principles and techniques using a tutorial approach in which students read, critique, and analyze over 75 actual experiments from every major area of psychology. She provides them with real-world information about how science in psychology is conducted and how they can participate. Recognizing that students come to an experimental design course with their own interests and perspectives, MacLin covers many subdisciplines of psychology throughout the text, including IO psychology, child psychology, social psychology, behavioral psychology, cognitive psychology, clinical psychology, health psychology, educational/school psychology, legal psychology, and personality psychology, among others. Part I of the text is content oriented and provides an overview of the principles of experimental design. Part II contains annotated research articles for students to read and analyze. Classic articles have been retained and 11 new ones have been added, featuring contemporary case studies, information on the Open Science movement, expanded coverage on ethics in research, and a greater focus on becoming a better writer, clarity and precision in writing, and reducing bias in language. This edition is up to date with the latest APA Publication Manual (7th edition) and includes an overview of the updated bias-free language guidelines, the use of singular "they," the new ethical compliance checklist, and other key changes in APA style. This text is essential reading for students and researchers interested in and studying experimental design in psychology.

This is the first book devoted to the use of social media and other internet-derived data in forming forensic clinical opinions of behavior. Designed for mental health practitioners, it outlines the challenges and the benefits of incorporating digital information in forensic assessments. It offers best practice guidelines geared to both criminal and civil psycho-legal questions. Each chapter includes a brief overview of the psycho-legal issues, clinical applications of consulting internet-based data, ethical and legal considerations and real life, de-identified case examples. This book provides guidance to the clinician in an emerging technological environment in which there are few resources, and ensures a more scientific and legally sound practice.

This brilliant CGP book covers all the maths skills needed in AS and A-Level Psychology (the use of maths is required for up to 10% of the marks in the final exams and assessments). It explains Calculations, Graph Skills and Statistics, with clear study notes and step-by-step examples in the context of Psychology. And to make sure you've really got to grips with it all, there are practice questions for each topic - with answers included at the back of the book.

This latest edition has been fully updated to accommodate the needs of users of SPSS Releases 17, 18 and 19 while still being applicable to users of SPSS Releases 15 and 16. As with previous editions, Alan Bryman and Duncan Cramer continue to offer a comprehensive and user-friendly introduction to the widely used IBM SPSS Statistics. The simple, non-technical approach to quantitative data analysis enables the reader to quickly become familiar with SPSS and with the tests available to them. No previous experience of statistics or computing is required as this book provides a step-by-step guide to statistical techniques, including: Non-parametric tests Correlation Simple and multiple regression Analysis of variance and covariance Factor analysis. This book comes equipped with a comprehensive range of exercises for further practice, and it covers key issues such as sampling, statistical inference, conceptualization and measurement and selection of appropriate tests. The authors have also included a helpful glossary of key terms. The data sets used in Quantitative Data Analysis with IBM SPSS 17, 18 and 19 are available online at http://www.routledgetextbooks.com/textbooks/_author/bryman-9780415579193/; in addition, a set of multiple-choice questions and a chapter-by-chapter PowerPoint lecture course are available free of charge to lecturers who adopt the book.

One of the greatest changes in the sports world in the past 20 years has been the use of mathematical methods to analyze performances, recognize trends and patterns, and predict results. Analytic Methods in Sports: Using Mathematics and Statistics to Understand Data from Baseball, Football, Basketball, and Other Sports, Second Edition provides a concise yet thorough introduction to the analytic and statistical methods that are useful in studying sports. The book gives you all the tools necessary to answer key questions in sports analysis. It explains how to apply the methods to sports data and interpret the results, demonstrating that the analysis of sports data is often different from standard statistical analyses. The book integrates a large number of motivating sports examples throughout and offers guidance on computation and suggestions for further reading in each chapter. Features Covers numerous statistical procedures for analyzing data based on sports results Presents fundamental methods for describing and summarizing data Describes aspects of probability theory and basic statistical concepts that are necessary to understand and deal with the randomness inherent in sports data Explains the statistical reasoning underlying the methods Illustrates the methods using real data drawn from a wide variety of sports Offers many of the datasets on the author's website, enabling you to replicate the analyses or conduct related analyses New to the Second Edition R code included for all calculations A new chapter discussing several more advanced methods, such as binary response models, random effects, multilevel models, spline methods, and principal components analysis, and more Exercises added to the end of each chapter, to enable use for courses and self-study Full solutions manual available to course instructors.

Modern Applied Regressions creates an intricate and colorful mural with mosaics of categorical and limited response variable (CLRV) models using both Bayesian and Frequentist approaches. Written for graduate students, junior researchers, and quantitative analysts in behavioral, health, and social sciences, this text provides details for doing Bayesian and frequentist data analysis of CLRV models. Each chapter can be read and studied separately with R coding snippets and template interpretation for easy replication. Along with the doing part, the text provides basic and accessible statistical theories behind these models and uses a narrative style to recount their origins and evolution. This book first scaffolds both Bayesian and frequentist paradigms for regression analysis, and then moves onto different types of categorical and limited response variable models, including binary, ordered, multinomial, count, and survival regression. Each of the middle four chapters discusses a major type of CLRV regression that subsumes an array of important variants and extensions. The discussion of all major types usually begins with the history and evolution of the prototypical model, followed by the formulation of basic statistical properties and an elaboration on the doing part of the model and its extension. The doing part typically includes R codes, results, and their interpretation. The last chapter discusses advanced modeling and predictive techniques-multilevel modeling, causal inference and propensity score analysis, and machine learning-that are largely built with the toolkits designed for the CLRV models previously covered. The online resources for this book, including R and Stan codes and supplementary notes, can be accessed at https://sites.google.com/site/socjunxu/home/statistics/modern-applied-regressions.

This book focuses on the use of the Rasch measurement model in validation studies and in analyzing the psychometric properties of a variety of test instruments, questionnaires, and scales in international contexts. It broadly examines the development and application of Rasch modeling, providing in-depth analyses of the properties of various scales used in the fields of education, and humanities and social sciences research. The book includes exemplary works on educational research and practices that highlight recent and innovative applications, as well as theoretical and practical aspects of Rasch modeling. Readers will find it helpful to understand the latest approaches to Rasch measurement in educational research, as well as practices for future studies and quantitative research. 'This book provides a diverse set of perspectives on Rasch models from scholars across the globe. The volume is both theoretical and applied. The first section of the book provides an overview of Rasch modeling and explains the theoretical and conceptual framework underlying the Rasch model. The remainder of the book highlights multiple applications of the Rasch model within educational assessment as well as several examples of how Rasch modeling can be used for validation studies. This volume showcases the wide variety of ways in which Rasch modeling can be applied to assessment data to provide insights into students' achievement and learning and to improve instruction.'-Betsy McCoach, University of Connecticut, USA. 'A well-written collection of articles. Grouped by the theoretical and applied aspects of Rasch measurement, each chapter in this edited volume makes notable contributions to knowledge and practice. Written by leading scholars in the field, these chapters were written in a clear, succinct, and assertive manner, providing readers with up-to-date information, analyses, and debates. This book should be found in the core collection of emerging researchers and established scholars in educational measurement.'-Timothy Teo, Murdoch University, Australia.

This book applies a range of ideas about scientific discovery found in contemporary philosophy of science to psychology and related behavioral sciences. In doing so, it aims to advance our understanding of a host of important methodological ideas as they apply to those sciences. A philosophy of local scientific realism is adopted in favor of traditional accounts that are thought to apply to all sciences. As part of this philosophy, the implications of a commitment to philosophical naturalism are spelt out, and a correspondence theory of truth is defended by showing how it helps explain various features of scientific practice. The central chapter of the book presents a broad theory of scientific method that comprises the detection of empirical phenomena and their subsequent understanding by constructing explanatory theories through the use of abductive methods. This theory of scientific method is then used as a framework to reconstruct the well-known qualitative method of grounded theory, and to present a systematic perspective on clinical reasoning and case formulation. Relatedly, an abductive or explanationist understanding of methods is employed to evaluate the knowledge credentials of evolutionary psychology. In addition, the conceptual and methodological foundations of a variety of quantitative methods are examined. Exploratory factor analysis and tests of statistical significance are given special attention.

Robert Guion's best seller is now available in this new second edition. This noted book offers a comprehensive and practical view of assessment -based personnel decisions not available elsewhere in a single source. This edition more frankly evaluates the current research and practice and presents challenges that will change the basic thinking about staffing systems. This new edition suggests new directions for research and practice, includes emphasis on modern computers and technology useful in assessment, and pays more attention to prediction of individual growth and globalization challenges in the assessment process. The book will be of interest to faculty and students in Industrial Organizational psychology, human resource management and business. IO psychologists in private business and public sector organizations who have responsibilities for staffing and an interest in measurement and statistics will find this book useful.

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.

Research Methods, Statistics, and Applications by Kathrynn A. Adams and Eva K. McGuire is designed to give students the experience of being a researcher by combining the interrelated concepts of research methods and statistics to better explain how the research process incorporates both elements. Employing a conversational tone throughout, coupled with an emphasis on decision-making, this best-selling text will spark students' interest in conducting research and improve their ability to critically analyze research in their daily lives. The Third Edition includes a new chapter on measurement to better highlight its critical importance, updates for the 7th edition of the Publication Manual of the American Psychological Association, new examples related to social justice, additional sections on qualitative research methods, and more thorough integration of research ethics information and tips throughout each chapter.

This Element describes noteworthy developments in cross-cultural psychology of the past half century. It stresses the author's involvement with the Journal of Cross-Cultural Psychology and the International Association for Cross-Cultural Psychology. It presents events in a decade-by-decade format, allowing brief discussion of high points in each decade, such as significant conferences and books, and commentaries on selected scholars. Topics include summaries of IACCP conferences, Online Readings in Psychology and Culture, IACCP Archives, and assessment of introductory psychology texts and their cultural content. Key aspects of culture-centered methodology in psychology and the teaching of culture-oriented psychology conclude the presentation.

Organized according to the sequence mental health professionals follow when conducting an assessment, Groth-Marnat s Handbook of Psychological Assessment, Sixth Edition covers principles of assessment, evaluation, referral, treatment planning, and report writing. Written in a practical, skills-based manner, the Sixth Edition provides guidance on the most efficient methods for selecting and administering tests, interpreting assessment data, how to integrate test scores and develop treatment plans as well as instruction on ways to write effective, client-oriented psychological reports. This text provides through coverage of the most commonly used assessment instruments including the Wechsler Intelligence Scales, Wechsler Memory Scales, Minnesota Multiphasic Personality Inventory, Personality Assessment Inventory, Millon Clinical Multiaxial Inventory, NEO Personality, Rorschach, Thematic Apperception Test, and brief assessment instruments for treatment planning, monitoring, and outcome assessment.

Psychic Retreats are states of mind to which patients can withdraw to evade anxiety and mental pain. The patient who does so excessively gets drawn into a tight knit web of relationships which become organised into a complex structure called a pathological organisation of the personality. This leads to the patient being "stuck" in their life and in their analysis. Using current Kleinian theory, John Steiner examines how Psychic Retreats are constructed and how analysts can treat them.

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This volume offers insights into contemporary trends and perspectives in psychobiographical research. It applys new theoretical and methodological frameworks and presents discourses on psychobiography from transdisciplinary backgrounds and various socio-cultural contexts, displaying the new state-of-the-art, new trends and themes in psychobiography. The book outlines psychobiography's outstanding contribution to psychology from 36 internationally reputable authors. It also presents the ideas of five outstanding psychobiographers through interview excerpts. This book is a must for researchers, lecturers and practitioners in the field of psychology and social sciences interested in the use of new psychological theories and methodologies in life-span research.

Secondary Data in Mixed Methods Research by Daphne C. Watkins, the latest contribution to the Mixed Methods Research Series, offers unique and necessary instruction in this growing topic. With the increasing amount of secondary data available through journals and repositories, researchers have a trove of sources for new investigations at their fingertips, but few books to guide them. This brief text provides readers with a step-by-step procedure for incorporating secondary data into various mixed methods research designs, as well as identifying key characteristics of existing datasets that make them good candidates for mixed methods projects and giving ideas for new uses of secondary data. Introductory chapters help the reader understand the "what" and "why" of secondary data. Subsequent chapters address the use of secondary data in convergent, exploratory sequential, explanatory sequential, and other complex research designs. The final chapters delve into writing and reporting on projects before, during, and after the project. Quotes throughout the chapter help readers remember key bits of knowledge, while learning objectives and summaries in each chapter structure the reading experience. Application questions at the end of each chapter help readers recall information and apply it to their own research projects. By emphasizing how to use existing qualitative and quantitative datasets in mixed methods research, Secondary Data in Mixed Methods Research will help readers answer new and ongoing questions in social science research.

This step-by-step guide is written for R and latent variable model (LVM) novices. Utilizing a path model approach and focusing on the lavaan package, this book is designed to help readers quickly understand LVMs and their analysis in R. The author reviews the reasoning behind the syntax selected and provides examples that demonstrate how to analyze data for a variety of LVMs. Featuring examples applicable to psychology, education, business, and other social and health sciences, minimal text is devoted to theoretical underpinnings. The material is presented without the use of matrix algebra. As a whole the book prepares readers to write about and interpret LVM results they obtain in R. Each chapter features background information, boldfaced key terms defined in the glossary, detailed interpretations of R output, descriptions of how to write the analysis of results for publication, a summary, R based practice exercises (with solutions included in the back of the book), and references and related readings. Margin notes help readers better understand LVMs and write their own R syntax. Examples using data from published work across a variety of disciplines demonstrate how to use R syntax for analyzing and interpreting results. R functions, syntax, and the corresponding results appear in gray boxes to help readers quickly locate this material. A unique index helps readers quickly locate R functions, packages, and datasets. The book and accompanying website at http://blogs.baylor.edu/rlatentvariable/ provides all of the data for the book's examples and exercises as well as R syntax so readers can replicate the analyses. The book reviews how to enter the data into R, specify the LVMs, and obtain and interpret the estimated parameter values. The book opens with the fundamentals of using R including how to download the program, use functions, and enter and manipulate data. Chapters 2 and 3 introduce and then extend path models to include latent variables. Chapter 4 shows readers how to analyze a latent variable model with data from more than one group, while Chapter 5 shows how to analyze a latent variable model with data from more than one time period. Chapter 6 demonstrates the analysis of dichotomous variables, while Chapter 7 demonstrates how to analyze LVMs with missing data. Chapter 8 focuses on sample size determination using Monte Carlo methods, which can be used with a wide range of statistical models and account for missing data. The final chapter examines hierarchical LVMs, demonstrating both higher-order and bi-factor approaches. The book concludes with three Appendices: a review of common measures of model fit including their formulae and interpretation; syntax for other R latent variable models packages; and solutions for each chapter's exercises. Intended as a supplementary text for graduate and/or advanced undergraduate courses on latent variable modeling, factor analysis, structural equation modeling, item response theory, measurement, or multivariate statistics taught in psychology, education, human development, business, economics, and social and health sciences, this book also appeals to researchers in these fields. Prerequisites include familiarity with basic statistical concepts, but knowledge of R is not assumed.

Starting from the preliminaries and ending with live examples, Modern Survey Sampling details what a sample can communicate about an unknowable aggregate in a real situation. The author lucidly develops and presents numerous approaches. He details recent developments and explores fresh and unseen problems, hitting upon possible solutions. The text covers current research output in a student-friendly manner with attractive illustrations. It introduces sampling and discusses how to select a sample for which a selection-probability is specified to prescribe its performance characteristics. The author then explains how to examine samples with varying probabilities to derive profits. He then examines how to use partial segments to make reasonable guesses about a sample's behavior and assess the elements of discrepancies. Including case studies, exercises, and solutions, the book highlights special survey techniques needed to capture trustworthy data and put it to intelligent use. It then discusses the model-assisted approach and network sampling, before moving on to speculating about random processes. The author draws on his extensive teaching experience to create a textbook that gives your students a thorough grounding in the technologies of survey sampling and modeling and also provides you with the tools to teach them.

Fully updated to reflect the latest developments, the third edition of Research Methods In Clinical Psychology offers a comprehensive introduction to the various methods, approaches, and strategies for conducting research in the clinical psychology field. * Represents the most accessible, user-friendly introduction to conducting and evaluating research for clinical psychologists and related professionals * Ideal for students and practitioners who wish to conduct their own research or gain a better understanding of published research * Addresses important issues such as philosophical underpinnings of various methodologies, along with socio-political issues that arise in clinical and community settings * Step-by-step guidance through all phases of a clinical psychology research project from initial concept and groundwork, through to measurement, design, analysis, and interpretation * Updates to this edition include new or expanded coverage of such topics as systematic review and literature searching methods, modern psychometric methods, guidance on choosing between different qualitative approaches, and conducting psychological research via the Internet

BASIC STATISTICS FOR THE BEHAVIORAL SCIENCES, International Edition demystifies and fully explains statistics without leaving out relevant topics or simply presenting formulas, in a format that is non-threatening and inviting to students. The author's clear, patiently crafted explanations, with an occasional touch of humor, teach students not only how to compute an answer, but also why they should perform the procedure or what their answer reveals about the data. The book achieves several objectives: it presents a conceptual-intuitive approach, presents statistics within an understandable research context, deals directly and positively with student weaknesses in mathematics, and introduces new terms and concepts in an integrated way. The result is a text that students can learn from as well as enjoy.

This book discusses the psychological traits associated with drug consumption through the statistical analysis of a new database with information on 1885 respondents and use of 18 drugs. After reviewing published works on the psychological profiles of drug users and describing the data mining and machine learning methods used, it demonstrates that the personality traits (five factor model, impulsivity, and sensation seeking) together with simple demographic data make it possible to predict the risk of consumption of individual drugs with a sensitivity and specificity above 70% for most drugs. It also analyzes the correlations of use of different substances and describes the groups of drugs with correlated use, identifying significant differences in personality profiles for users of different drugs. The book is intended for advanced undergraduates and first-year PhD students, as well as researchers and practitioners. Although no previous knowledge of machine learning, advanced data mining concepts or modern psychology of personality is assumed, familiarity with basic statistics and some experience in the use of probabilities would be helpful. For a more detailed introduction to statistical methods, the book provides recommendations for undergraduate textbooks.

This book explores test adaptation, a scientific and professional activity now spanning all of the social and behavioural sciences. Adapting tests to various linguistic and cultural contexts is a critical process in today's globalized world, and requires a combination of knowledge and skills from psychometrics, cross-cultural psychology and others. This volume provides a step-by-step approach to cross-cultural test adaptation, emphatically presented as a melange between science and practice. The volume is driven by the first-hand practical experience of the author in a large number of test adaptation projects in various cultures, and is supported by the consistent scientific body of knowledge accumulated over the last several decades on the topic. It is the first of its kind: an in-depth treatise and guide on why and how to adapt a test to a new culture in such a way as to preserve its psychometric value.