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

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

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

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

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

Welcome to the world of psychology--and a journey through the gateways to mind and behavior. Led by authors who get rave reviews from students and instructors alike, this text integrates a proven system for reflective learning: Survey, Question, Read, Reflect, Review and Recite. By following these steps for efficient studying, you can master Psychology's concepts and explore its diversity of topics that are relevant to today's world. Active learning tools are interspersed with examples and anecdotes in a conversational style, along with coverage of the field's newest research findings. Experience the fun of discovering Psychology with INTRODUCTION TO PSYCHOLOGY: GATEWAYS TO MIND AND BEHAVIOR, 15th Edition.

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.

Bodies that Birth puts birthing bodies at the centre of questions about contemporary birth politics, power, and agency. Arguing that the fleshy and embodied aspects of birth have been largely silenced in social science scholarship, Rachelle Chadwick uses an array of birth stories, from diverse race-class demographics, to explore the narrative entanglements between flesh, power, and sociomateriality in relation to birth. Adopting a unique theoretical framework incorporating new materialism, feminist theory, and a Foucauldian 'analytics of power', the book aims to trace and trouble taken-for-granted assumptions about birthing bodies. Through a diffractive and dialogical approach, the analysis highlights the interplay between corporeality, power, and ideologies in the making of birth narratives across a range of intersectional differences. The book shows that there is no singular birthing body apart from sociomaterial relations of power. Instead, birthing bodies are uncertain zones or unpredictable assortments of physiology, flesh, sociomateriality, discourse, and affective flows. At the same time, birthing bodies are located within intra-acting fields of power relations, including biomedicine, racialized patriarchy, socioeconomics, and geopolitics. Bodies that Birth brings the voices of women from different sociomaterial positions into conversation. Ultimately, the book explores how attending to birthing bodies can vitalize global birth politics by listening to what matters to women in relation to birth. This is fascinating reading for researchers, academics, and students from across the social sciences.

Students can find statistical analysis a challenging and complex task and, in order to master the techniques and complete their assignments and projects successfully, they need to have a sound understanding of IBM SPSS and its functions. Updated to be compatible with IBM SPSS 25, with handy screen-shots throughout, the seventh edition of this trusted and practical textbook will take students on a step-by-step journey towards carrying out a range of essential tasks with confidence: from performing an analysis to interpreting outputs and reporting the results. This book is an unbeatable, must-have guide to IBM SPSS that will allow undergraduate psychology students to master this powerful software tool. Accompanying online resources for this title can be found at bloomsburyonlineresources.com/spss-for-psychologists. These resources are designed to support teaching and learning when using this textbook and are available at no extra cost.

Software is cut and dried - every button you press has a predictable effect - but qualitative analysis is open ended and unfolds in unpredictable ways. This contradiction is best resolved by separating analytic strategies - what you plan to do - from software tactics - how you plan to do it. Expert NVivo users have unconsciously learned to do this. The Five-Level QDA (R) method unpacks the process so that you can learn it consciously and efficiently. The first part of the book explains how the contradiction between analytic strategies and software tactics is reconciled by "translating" between them. The second part provides both an in-depth description of how NVivo works and comprehensive instruction in the five steps of "translation". These steps are illustrated with examples from a variety of research projects. The third part contains real-world qualitative research projects from a variety of disciplines, methodologies, and kinds of qualitative analysis, all illustrated in NVivo using the Five-Level QDA method. The book is accompanied by three sets of video demonstrations on the companion website. The book and accompanying videos illustrate the Windows version of NVivo. As there are some differences in screen and interface design between the Mac and Windows versions please watch the video 'The NVivo Mac Interface' in the Component Orientation series of videos (available on the companion website). The Five-Level QDA method is based on the authors' combined 40 years of experience teaching NVivo and other software packages used as platforms for conducting qualitative analysis. After many years observing their students' challenges they developed the Five-Level QDA method to describe the process that long-time NVivo experts unconsciously adopt. The Five-Level QDA method is independent of software program or methodology, and the principles apply to any type of qualitative project. Please see the following URL to access the accompanying materials for this book: https://www.qdaservices.co.uk/five-level-qda

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

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

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

Contents include:

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

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

This book seeks to re-define the role of fantasy in human life by overturning mainstream psychology's understanding of daydreams as being task-distracted mind wandering by proposing that all waking fantasies function to transform mood states into specific emotional reactions.

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.

Data Analysis: A Model Comparison Approach to Regression, ANOVA, and Beyond is an integrated treatment of data analysis for the social and behavioral sciences. It covers all of the statistical models normally used in such analyses, such as multiple regression and analysis of variance, but it does so in an integrated manner that relies on the comparison of models of data estimated under the rubric of the general linear model. Data Analysis also describes how the model comparison approach and uniform framework can be applied to models that include product predictors (i.e., interactions and nonlinear effects) and to observations that are nonindependent. Indeed, the analysis of nonindependent observations is treated in some detail, including models of nonindependent data with continuously varying predictors as well as standard repeated measures analysis of variance. This approach also provides an integrated introduction to multilevel or hierarchical linear models and logistic regression. Finally, Data Analysis provides guidance for the treatment of outliers and other problematic aspects of data analysis. It is intended for advanced undergraduate and graduate level courses in data analysis and offers an integrated approach that is very accessible and easy to teach. Highlights of the third edition include: a new chapter on logistic regression; expanded treatment of mixed models for data with multiple random factors; updated examples; an enhanced website with PowerPoint presentations and other tools that demonstrate the concepts in the book; exercises for each chapter that highlight research findings from the literature; data sets, R code, and SAS output for all analyses; additional examples and problem sets; and test questions.

NOTE: This edition features the same content as the traditional text in a convenient, three-hole-punched, loose-leaf version. Books a la Carte also offer a great value; this format costs significantly less than a new textbook. Before purchasing, check with your instructor or review your course syllabus to ensure that you select the correct ISBN. For courses in introductory psychology, critical thinking, and research and experimental methods. Market-leading consumer's guide to assessing psychological claims Widely used and highly acclaimed, How to Think Straight About Psychology introduces students to the critical thinking skills they need to independently evaluate psychological information. Students will learn to analyze psychological claims found in the media, distinguish between pseudoscience and true psychological research, and apply psychological knowledge to the world around them. The 11th edition covers an extensive range of new topics and examples illustrating psychological principles, pseudoscience, and issues obscuring the real and growing knowledge base in the field of psychology.

This approachable guide meets health and social sciences scholars at their level-either as a reference text or as an enchanting but practical read-and walks them through each stage of their academic publishing journey. Drawing on a wealth of examples from his own experience mentoring others and publishing 300+ articles, Dr. Schwartz engages early, mid-, and senior-level professionals as well as graduate students and postdoctoral fellows alike, to demystify each stage of the writing and publishing process. Employing a reader-friendly, accessible voice, Dr. Schwartz's style captivates readers across disciplines, with a refreshing, can-do perspective. Before diving in, the author relates his own personal story in scholarly publishing, inviting all academics to unlock the high-impact writer within. The next set of chapters tackle the nuts and bolts of the academic publishing process, with basics such as topic selection, data analysis for publication, writing preparation, drafting and editing manuscripts, and journals submissions. The book advances into more innovative topics that can be simultaneously intimidating and rewarding, including recruiting and collaborating with coauthors, developing a network, navigating the peer review process, publishing nonempirical papers, getting creative with rejected manuscripts, foraying into Open Access and fee-based publishing, and even how to publish a book or book chapter. Designed as a digital mentor, The Savvy Academic is the ultimate tool for students, fellows, and scholarly professionals of a broad range of experiences in the health and social sciences who are looking to launch or elevate their scholarly publication career.

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

Alan C. Acock's A Gentle Introduction to Stata, Revised Sixth Edition is aimed at new Stata users who want to become proficient in Stata. After reading this introductory text, new users will be able to not only use Stata well but also learn new aspects of Stata. Acock assumes that the user is not familiar with any statistical software. This assumption of a blank slate is central to the structure and contents of the book. Acock starts with the basics; for example, the part of the book that deals with data management begins with a careful and detailed example of turning survey data on paper into a Stata-ready dataset. When explaining how to go about basic exploratory statistical procedures, Acock includes notes that will help the reader develop good work habits. This mixture of explaining good Stata habits and explaining good statistical habits continues throughout the book. Acock is quite careful to teach the reader all aspects of using Stata. He covers data management, good work habits (including the use of basic do-files), basic exploratory statistics (including graphical displays), and analyses using the standard array of basic statistical tools (correlation, linear and logistic regression, and parametric and nonparametric tests of location and dispersion). He also successfully introduces some more advanced topics such as multiple imputation and multilevel modeling in a very approachable manner. Acock teaches Stata commands by using the menus and dialog boxes while still stressing the value of Stata commands and do-files. In this way, he ensures that all types of users can build good work habits. Each chapter has exercises that the motivated reader can use to reinforce the material. The tone of the book is friendly and conversational without ever being glib or condescending. Important asides and notes about terminology are set off in boxes, which makes the text easy to read without any convoluted twists or forward referencing. Rather than splitting topics by their Stata implementation, Acock arranges the topics as they would appear in a basic statistics textbook; graphics and postestimation are woven into the material naturally. Real datasets, such as the General Social Surveys from 2002, 2006, and 2016, are used throughout the book. The focus of the book is especially helpful for those in the behavioral and social sciences because the presentation of basic statistical modeling is supplemented with discussions of effect sizes and standardized coefficients. Various selection criteria, such as semipartial correlations, are discussed for model selection. Acock also covers a variety of commands available for evaluating reliability and validity of measurements. The revised sixth edition is fully up to date for Stata 17, including updated discussion and images of Stata's interface and modern command syntax. In addition, examples include new features such as the table command and collect suite for creating and exporting customized tables as well as the option for creating graphs with transparency.

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

The new edition features:

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

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

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

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

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

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

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

This unique book provides a comprehensive and detailed coverage of configural frequency analysis (CFA), the most useful method of analysis of categorical data in person-oriented research. It presents the foundations, methods, and models of CFA and features numerous empirical data examples from a range of disciplines that can be reproduced by the readers. It also addresses computer applications, including relevant R packages and modules. Configural frequency analysis is a statistical method that allows the processing of important and interesting questions in categorical data. The perspective of CFA differs from the usual perspective of relations among variables; its focus is on patterns of variable categories that stand out with respect to specific hypotheses, and as such, CFA allows for testing numerous substantive hypotheses. The book describes the origins of CFA and their relation to chi-square analysis as well as the developments that are based on log-linear modeling. The models covered range from simple models of variable independence to complex models that are needed when causal hypotheses are tested. Empirical data examples are provided for each model. New models are introduced for person-oriented mediation analysis and locally optimized time series analysis, and new results concerning the characteristics of CFA methods are bolstered using Monte Carlo simulations. Primarily intended for researchers and students in the social and behavioral sciences, the book will also appeal to anyone who deals with categorical data from a person-centered perspective.

This book presents an update on social psychology as a disciplinary space and research field. First, it discusses the irruption of research methods from other cultural niches in the instituted academic area. Then, the second and third chapters discuss the role of Critical Psychology for community emancipation in hybrid settings and the development of Vygotsky's theory in Latin America. The fourth and fifth chapters offer some questions on contemporary legal and political culture. The sixth and seventh chapters ask how to reconceptualise the studies on Social Imaginary amd childhood. The eighth and ninth chapters present topics as performativity, cybernetic, subjectivities, and technology networks in health-related social support. In the last chapter, the author asks: are networks a cause of the human condition or a result of it? Is virtuality a condition and, at the same time, a result of the human? What could offer a psychoanalytic ethnographic approach to recover the concept of being human as the experience of intimate bonding as part of a social network?

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

This comprehensive guide offers a rich introduction to research methods, experimental design and data analysis techniques in developmental science, emphasizing the importance of an understanding of this area of psychology for any student or researcher interested in examining development across the lifespan. The expert contributors enhance the reader's knowledge base, understanding of methods, and critical thinking skills in their area of study. They cover development from the prenatal period to adolescence and old age, and explore key topics including the history of developmental research, ethics, animal models, physiological measures, eye-tracking, and computational and robotics models. They accessibly explore research measures and design in topics including gender identity development, the influence of neighborhoods, mother-infant attachment relationships, peer relationships in childhood, prosocial and moral development patterns, developmental psychopathology and social policy, and the examination of memory across the lifespan. Each chapter ends with a summary of innovations in the field over the last ten years, giving students and interested researchers a thorough overview of the field and an idea of what more is to come. Conducting Research in Developmental Psychology is essential reading for upper-level undergraduate or graduate students seeking to understand a new area of developmental science, developmental psychology, and human development. It will also be of interest to junior researchers who would like to enhance their knowledge base in a particular area of developmental science, human development, education, biomedical science, or nursing.

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