This book provides an illustrative overview of some of the key methodological and technical innovations that form the cutting edge of current research in behavioral medicine. It is divided into three sections. Part I consists of six chapters describing the impact on behavioral medicine research of novel developments in diverse areas such as molecular genetics, neuroendocrine assessment, laboratory radionuclide measurement of cardiac function, and the development of electronic event monitors for measuring compliance with medication regimens. In addition, new applications of long-available assessment techniques in clinical neuropsychology to behavioral issues in cardiovascular disease are reviewed. Part II includes four chapters which review methods and programs of research dealing with aspects of the ambulatory monitoring of moods and behavioral activities in conjunction with a variety of physiological processes and/or disease states. Finally, Part III provides two chapters which focus on novel theoretical and/or conceptual approaches--instead of the typical methodological innovations--that have guided recent research in behavioral oncology and in cardiovascular disease and the clustering syndrome of cardiovascular risk factors that relate to insulin metabolism.

For several decades there has been an increasing move towards viewing the psychotic illnesses from a dimensional perspective, seeing them as continuous with healthy functioning. The idea, concentrating mostly on schizophrenia, has generated considerable theoretical debate as well as empirical research, conducted under the rubric of 'schizotypy'. This book offers a timely discussion of the most significant themes and developments in this research area. Divided into four key sections which represent current concerns in schizotypy research - Measurement, Brain and Biology; Development and Environment; Consequences and Outcomes; and Future Directions - chapters reflect a broad range of approaches and discuss varied theoretical perspectives on schizotypy. Topics include: cognitive and perceptual biases psychometric assessments creativity and schizotypy genetic associations. developmental perspectives Schizotypy: New dimensions will appeal to academics, researchers and postgraduate students in the area of psychotic illnesses, as well as professionals including psychiatrists and clinical psychologists who are concerned with the basis of serious mental disorder. The book will inform readers who are new to the topic and will update and expand the knowledge base of those more experienced in the field.

The Psychology Research Companion: From student project to working life not only gives you the skills and confidence to conduct your psychology research project at university, but is the first book to show how these skills will help you get ahead in your first job in the workplace. Jessica S. Horst, an American psychologist teaching in the UK, takes you through every step of the research process; from conceiving your research question and choosing a research methodology, to organizing your time and resources effectively. The book includes sections on ethics, data management, working with research participants and report writing, but each chapter is also informed by the wider aim of providing a toolkit for working life. Each chapter is packed with tips and skills that can be taken into the workplace, including working collaboratively and organising your workload, as well as discussing your research project in interview situations and when applying for jobs. This invaluable guide will appeal to all undergraduate and postgraduate psychology students whose aim is to learn a set of transferable research skills as well as to obtain a good degree result.

Learn How to Infuse Leadership into Your Passion for Scientific Research Leadership and Women in Statistics explores the role of statisticians as leaders, with particular attention to women statisticians as leaders. By paying special attention to women's issues, this book provides a clear vision for the future of women as leaders in scientific and technical fields. It also shows how emerging and current leaders of both genders in many disciplines can expand their leadership potentials. Featuring contributions from leadership experts and statisticians at various career stages, this unique and insightful text: Examines leadership within the roles of statistician and data scientist from international and diverse perspectives Supplies a greater understanding of leadership within teams, research consulting, and project management Encourages reflection on leadership behaviors, promoting both natural and organizational leadership Identifies existing opportunities to foster creative outputs and develop strong leadership voices Includes real-life stories about overcoming barriers to leadership Leadership and Women in Statistics explains how to convert a passion for statistical science into visionary, ethical, and transformational leadership. Although the context focuses on statistics, the material applies to almost all fields of endeavor. This book is a valuable resource for those ready to consider leadership as an important element of their careers, and for those who are already leaders but want to deepen their perspectives on leadership. It makes an ideal text for group leadership training as well as for individual professional development.

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.

The Trouble with Twin Studies questions popular genetic explanations of human behavioral differences based upon the existing body of twin research. Psychologist Jay Joseph outlines the fallacies of twin studies in the context of the ongoing decades-long failure to discover genes for human behavioral differences, including IQ, personality, and the major psychiatric disorders. This volume critically examines twin research, with a special emphasis on reared-apart twin studies, and incorporates new and updated perspectives, analyses, arguments, and evidence.

Plenty of literature review and applications of various tests provided to cover all the aspects of research methodology Various examination questions have been provided Strong Pedagogy along with regular features such as Concept Checks, Text Overviews, Key Terms, Review Questions, Exercises and References Though the book is primarily addressed to students,it will be equally useful to Researchers and Entrepreneurs More than other research textbooks, this book addresses the students' need to comprehend all aspects of the research process which includes Research process, clarification of the research problem, Ethical issues, Survey research, Research report preparation and presentation.

This groundbreaking edited book, The Routledge Handbook for Advancing Integration in Mixed Methods Research, presents an array of different integration ideas, with contributions from scholars across the globe. This handbook represents the first major volume that comprehensively discusses this topic of integration. Perhaps the most fundamental and longstanding question in mixed methods research is: How does one best integrate disparate forms of information to produce the best form of inquiry? Each of the 34 seminal chapters in this handbook accelerates the discussion of integration across a broad range of disciplines, including education, arts-based analyses, and work in the Global South, as well as special topics such as psychometrics and media research. Many of the chapters present new topics that have never been written about before, and all chapters offer cutting-edge approaches to integration. They also offer different perspectives of integration - leading the introductory chapter to offer a new and comprehensive definition for integration, as follows: "referring to the optimal mixing, combining, blending, amalgamating, incorporating, joining, linking, merging, consolidating, or unifying of research approaches, methodologies, philosophies, methods, techniques, concepts, language, modes, disciplines, fields, and/or teams within a single study." The concluding chapter offers a meta-framework that accounts for this definition and is designed to help scholars think more about integration in a way that represents a continuous, dynamic, iterative, interactive, synergistic, and holistic meaning-making process. This handbook will be an essential reference work for all scholars and practitioners using or seeking to use mixed methods in their research.

Written specifically for those with no prior programming experience and minimal quantitative training, this accessible text walks behavioral science students and researchers through the process of programming using MATLAB. The book explores examples, terms, and programming needs relevant to those in the behavioral sciences and helps readers perform virtually any computational function in solving their research problems. Principles are illustrated with usable code. Each chapter opens with a list of objectives followed by new commands required to accomplish those goals. These objectives also serve as a reference to help readers easily relocate a section of interest. Sample code and output and chapter problems demonstrate how to write a program and explore a model so readers can see the results obtained using different equations and values. A web site provides solutions to selected problems and the book's program code output and examples so readers can manipulate them as needed. The outputs on the website have color, motion, and sound. Highlights of the new edition include: *Updated to reflect changes in the most recent version of MATLAB, including special tricks and new functions. *More information on debugging and common errors and more basic problems in the rudiments of MATLAB to help novice users get up and running more quickly. *A new chapter on Psychtoolbox, a suite of programs specifically geared to behavioral science research. *A new chapter on Graphical User Interfaces (GUIs) for user-friendly communication. *Increased emphasis on pre-allocation of memory, recursion, handles, and matrix algebra operators. The book opens with an overview of what is to come and tips on how to write clear programs followed by pointers for interacting with MATLAB, including its commands and how to read error messages. The matrices chapter reviews how to store and access data. Chapter 4 examines how to carry out calculations followed by a review of how to perform various actions depending on the conditions. The chapter on input and output demonstrates how to design programs to create dialogs with users (e.g., participants in studies) and read and write data to and from external files. Chapter 7 reviews the data types available in MATLAB. Readers learn how to write a program as a stand-alone module in Chapter 8. In Chapters 9 and 10 readers learn how to create line and bar graphs or reshape images. Readers learn how to create animations and sounds in Chapter 11. The book concludes with tips on how to use MATLAB with applications such as GUIs and Psychtoolbox. Intended as a primary text for Matlab courses for advanced undergraduate and/or graduate students in experimental and cognitive psychology and/or neuroscience as well as a supplementary text for labs in data (statistical) analysis, research methods, and computational modeling (programming), the book also appeals to individual researchers in these disciplines who wish to get up and running in MATLAB.

Multiple Imputation in Practice: With Examples Using IVEware provides practical guidance on multiple imputation analysis, from simple to complex problems using real and simulated data sets. Data sets from cross-sectional, retrospective, prospective and longitudinal studies, randomized clinical trials, complex sample surveys are used to illustrate both simple, and complex analyses. Version 0.3 of IVEware, the software developed by the University of Michigan, is used to illustrate analyses. IVEware can multiply impute missing values, analyze multiply imputed data sets, incorporate complex sample design features, and be used for other statistical analyses framed as missing data problems. IVEware can be used under Windows, Linux, and Mac, and with software packages like SAS, SPSS, Stata, and R, or as a stand-alone tool. This book will be helpful to researchers looking for guidance on the use of multiple imputation to address missing data problems, along with examples of correct analysis techniques.

Interpreting Statistics for Beginners teaches readers to correctly read and interpret results of basic statistical procedures as they are presented in scientific literature, and to understand what they can and cannot infer from such results.

The first of its kind, this book explains key elements of scientific paradigms and philosophical concepts that the use of statistics is based on and introduces readers to basic statistical concepts, descriptive statistics and basic elements and procedures of inferential statistics. Explanations are accompanied with detailed examples from scientific publications to demonstrate how the procedures are used and correctly interpreted. Additionally, Interpreting Statistics for Beginners shows readers how to recognize pseudoscientific claims that use statistics or statements not based on the presented data, which is an important skill for every professional relying on statistics in their work.

Written in an easy-to-read style and focusing on explaining concepts behind statistical calculations, the book is most helpful for readers with no previous training in statistics, and also those wishing to bridge the conceptual gap between doing the statistical calculations and interpreting the results.

Nonparametric Models for Longitudinal Data with Implementations in R presents a comprehensive summary of major advances in nonparametric models and smoothing methods with longitudinal data. It covers methods, theories, and applications that are particularly useful for biomedical studies in the era of big data and precision medicine. It also provides flexible tools to describe the temporal trends, covariate effects and correlation structures of repeated measurements in longitudinal data. This book is intended for graduate students in statistics, data scientists and statisticians in biomedical sciences and public health. As experts in this area, the authors present extensive materials that are balanced between theoretical and practical topics. The statistical applications in real-life examples lead into meaningful interpretations and inferences. Features: * Provides an overview of parametric and semiparametric methods * Shows smoothing methods for unstructured nonparametric models * Covers structured nonparametric models with time-varying coefficients * Discusses nonparametric shared-parameter and mixed-effects models * Presents nonparametric models for conditional distributions and functionals * Illustrates implementations using R software packages * Includes datasets and code in the authors' website * Contains asymptotic results and theoretical derivations

Big Data for Qualitative Research covers everything small data researchers need to know about big data, from the potentials of big data analytics to its methodological and ethical challenges. The data that we generate in everyday life is now digitally mediated, stored, and analyzed by web sites, companies, institutions, and governments. Big data is large volume, rapidly generated, digitally encoded information that is often related to other networked data, and can provide valuable evidence for study of phenomena. This book explores the potentials of qualitative methods and analysis for big data, including text mining, sentiment analysis, information and data visualization, netnography, follow-the-thing methods, mobile research methods, multimodal analysis, and rhythmanalysis. It debates new concerns about ethics, privacy, and dataveillance for big data qualitative researchers. This book is essential reading for those who do qualitative and mixed methods research, and are curious, excited, or even skeptical about big data and what it means for future research. Now is the time for researchers to understand, debate, and envisage the new possibilities and challenges of the rapidly developing and dynamic field of big data from the vantage point of the qualitative researcher.

This is the first book to demonstrate the application of power analysis to the newer more advanced statistical techniques that are increasingly used in the social and behavioral sciences. Both basic and advanced designs are covered. Readers are shown how to apply power analysis to techniques such as hierarchical linear modeling, meta-analysis, and structural equation modeling. Each chapter opens with a review of the statistical procedure and then proceeds to derive the power functions. This is followed by examples that demonstrate how to produce power tables and charts. The book clearly shows how to calculate power by providing open code for every design and procedure in R, SAS, and SPSS. Readers can verify the power computation using the computer programs on the book's website. There is a growing requirement to include power analysis to justify sample sizes in grant proposals. Most chapters are self-standing and can be read in any order without much disruption.This book will help readers do just that. Sample computer code in R, SPSS, and SAS at www.routledge.com/9781848729810 are written to tabulate power values and produce power curves that can be included in a grant proposal. Organized according to various techniques, chapters 1 - 3 introduce the basics of statistical power and sample size issues including the historical origin, hypothesis testing, and the use of statistical power in t tests and confidence intervals. Chapters 4 - 6 cover common statistical procedures -- analysis of variance, linear regression (both simple regression and multiple regression), correlation, analysis of covariance, and multivariate analysis. Chapters 7 - 11 review the new statistical procedures -- multi-level models, meta-analysis, structural equation models, and longitudinal studies. The appendixes contain a tutorial about R and show the statistical theory of power analysis. Intended as a supplement for graduate courses on quantitative methods, multivariate statistics, hierarchical linear modeling (HLM) and/or multilevel modeling and SEM taught in psychology, education, human development, nursing, and social and life sciences, this is the first text on statistical power for advanced procedures. Researchers and practitioners in these fields also appreciate the book's unique coverage of the use of statistical power analysis to determine sample size in planning a study. A prerequisite of basic through multivariate statistics is assumed.

This approach gives the practical skills used by outstanding communicators. Excellent communication is the basis of creating excellent results. NLP skills are proving invaluable for personal development and professional excellence in counselling, education and business.Introducing NLP includes:• How to create rapport with others• Influencing skills• Understanding and using body language• How to think about and achieve the results you want• The art of asking key questions• Effective meetings, negotiations and selling• Accelerated learning strategies.

Unexpected events during an evaluation all too often send evaluators into crisis mode. This insightful book provides a systematic framework for diagnosing, anticipating, accommodating, and reining in costs of evaluation surprises. The result is evaluation that is better from a methodological point of view, and more responsive to stakeholders. Jonathan A. Morell identifies the types of surprises that arise at different stages of a program's life cycle and that may affect different aspects of the evaluation, from stakeholder relationships to data quality, methodology, funding, deadlines, information use, and program outcomes. His analysis draws on 18 concise cases from well-known researchers in a variety of evaluation settings. Morell offers guidelines for responding effectively to surprises and for determining the risks and benefits of potential solutions.

Polls are conducted every day all around the world for almost everything (especially during elections). But not every poll is a good one. A lot depends on the type of questions asked, how they are asked and whether the sample used is truly representative. And these are not the only aspects of a poll that should be checked. So how does one separate the chaff from the wheat? That's where Understanding Public Opinion Polls comes in. Written by a well-known author with over thirty years of experience, the book is built around a checklist for polls that describes the various aspects of polls to pay attention to if one intends to use its results. By comprehensively answering the questions in the checklist, a good idea of the quality of the poll is obtained. Features: Provides readers with a deeper understanding of practical and theoretical aspects of opinion polls while assuming no background in mathematics or statistics Shows how to determine if a poll is good or bad Provides a historical perspective and includes examples from real polls Gives special attention to online and election polls The book gives an overview of many aspects of polls - questionnaire design, sample selection, estimation, margins of error, nonresponse and weighting. It is essential reading for those who want to gain a better understanding of the ins and outs of polling including those who are confronted with polls in their daily life or work or those who need to learn how to conduct their own polls.

An overview is given of cross-cultural psychology and cultural psychology, focusing on theory and methodology. In Section 1 historical developments in research are traced; it is found that initially extensive psychological differences tend to shrink when more carefully designed studies are conducted. Section 2 addresses the conceptualization of "culture" and of "a culture". For psychological research the notion "culture" is considered too vague; more focal explanatory concepts are required. Section 3 describes methodological issues, taking the notion of the empirical cycle as a lead for both qualitative and quantitative research. Pitfalls in research design and data analysis of behavior-comparative studies, and the need for replication are discussed. Section 4 suggests to move beyond research on causal relationships and to incorporate additional questions, addressing the function and the development of behavior patterns in ontogenetic, phylogenetic and historical time. Section 5 emphasizes the need for applied research serving the global village.

* It offers an original answer to this question: evaluation spreads because we want to be evaluated. * Developing a critical reflection from a psychoanalytic perspective, it argues that workers are not mere victims of evaluation systems but are complicit in them. * Benedicte Vidaillet focuses on the aspects of our subjectivity that come into play in evaluation at work -our expectations, desires, need for recognition, our conceptions of ourselves at work, as well as our relationship with others such as colleagues, managers or clients - to explore how evaluation affects us, where it gets its evocative power, and what it stirs within us to make us want it, despite its detrimental effects in its currently practiced form. * Chapters draw on real-life examples, case studies from a variety of organizations, and observations from clinical practice, to provide insight into the many mechanisms that have enabled evaluation to spread unimpeded through our subjective complicity in the process, revealing how they came to seem so innocuous. * This book will be of interest to scholars studying the topic of evaluation at work from a critical perspective as well as professionals who use evaluation systems or are under the pressure of evaluation in all sectors and organizations. * By exposing the psychological mechanisms that evaluation uses to appeal to us, it gives each of us the tools we need to break free of its grasp.

The leading text that covers both the theory and practice of evaluation in one engaging volume has now been revised and updated with additional evaluation approaches (such as mixed methods and principles-focused evaluation) and new methods (such as technologically based strategies). The book features examples of small- and large-scale evaluations from a range of fields, many with reflective commentary from the evaluators; helpful checklists; and carefully crafted learning activities. Major theoretical paradigms in evaluation--and the ways they inform methodological choices--are explained. Readers learn effective strategies for clarifying their own theoretical assumptions; working with stakeholders; developing questions; using quantitative, qualitative, and mixed methods designs; selecting data collection and sampling strategies; analyzing data; and communicating and utilizing findings. The new companion website provides extensive recommended online resources and tools, organized by chapter. New to This Edition *Additional evaluation approaches: collaborative evaluation, principles-focused evaluation, and desk reviews. *Coverage of new data collection technologies and methods of qualitative coding. *Expanded discussions of logic models, cost-benefit analysis, and mixed methods designs. *Many new and updated sample studies. Pedagogical Features *Reflection questions that prepare students to read each chapter. *"Extending Your Thinking" questions and practical activities. *Boxes delving into key concepts and example studies. *End-of-book Glossary, and highlighted key terms throughout. *Companion website with links to helpful resources on all aspects of evaluation.

Contains information for using R software with the examples in the textbook Sampling: Design and Analysis, 3rd edition by Sharon L. Lohr.

In 2010, the International Cyberbullying Think Tank was held in order to discuss questions of definition, measurement, and methodologies related to cyberbullying research. The attendees goal was to develop a set of guidelines that current and future researchers could use to improve the quality of their research and advance our understanding of cyberbullying and related issues. This book is the product of their meetings, and is the first volume to provide researchers with a clear set of principles to inform their work on cyberbullying. The contributing authors, all participants in the Think Tank, review the existing research and theoretical frameworks of cyberbullying before exploring topics such as questions of methodology, sampling issues, methods employed so far, psychometric issues that must be considered, ethical considerations, and implications for prevention and intervention efforts. Researchers as well as practitioners seeking information to inform their prevention and intervention programs will find this to be a timely and essential resource.

Statistical Analysis of Contingency Tables is an invaluable tool for statistical inference in contingency tables. It covers effect size estimation, confidence intervals, and hypothesis tests for the binomial and the multinomial distributions, unpaired and paired 2x2 tables, rxc tables, ordered rx2 and 2xc tables, paired cxc tables, and stratified tables. For each type of table, key concepts are introduced, and a wide range of intervals and tests, including recent and unpublished methods and developments, are presented and evaluated. Topics such as diagnostic accuracy, inter-rater reliability, and missing data are also covered. The presentation is concise and easily accessible for readers with diverse professional backgrounds, with the mathematical details kept to a minimum. For more information, including a sample chapter and software, please visit the authors' website.

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

Studying Complex Interactions and Outcomes Through Qualitative Comparative Analysis: A Practical Guide to Comparative Case Studies and Ethnographic Data Analysis offers practical, methodological, and theoretically robust guidelines to systematically study the causalities, dynamics, and outcomes of complex social interactions in multiple source data sets. It demonstrates how to convert data from multisited ethnography of investment politics, mobilizations, and citizen struggles into a Qualitative Comparative Analysis (QCA). In this book, Markus Kroeger focuses on how data collected primarily via multisited political ethnography, supplemented by other materials and verified by multiple forms of triangulation, can be systematically analyzed through QCA. The results of this QCA offer insight on how to study the political and economic outcomes in natural resource conflicts, across different contexts and political systems. This book applies the method in practice using examples from the author's own research. With a focus on social movement studies, it shows how QCA can be used to analyze a multiple data source database, that includes results from multiple case studies. This book is a practical guide for researchers and students in social movement studies and other disciplines that produce ethnographic data from multiple sources on how to analyze complex databases through the QCA.