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.

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.

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.

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.

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.

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.

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.

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.

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.

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

* 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.

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.

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

The new edition of An Introduction to Statistical Concepts is designed to help students really understand statistical concepts, the situations in which they can be used, and how to apply them to data. Hahs-Vaughn and Lomax discuss the most popular, along with many of the lesser-known, procedures and models, whilst also exploring nonparametric procedures used when standard assumptions are violated. They provide in-depth coverage of testing assumptions and highlight several online tools for computing statistics (e.g., effect sizes and their confidence intervals and power). This comprehensive, flexible, and accessible text includes a new chapter on mediation and moderation; expanded coverage of effect sizes; and discussions of sensitivity, specificity, false positive, and false negative, along with using the receiver operator characteristic (ROC) curve. In addition to instructions and screen shots for using SPSS, new to this edition is annotated script for using R. This book, noted for its crystal-clear explanations, and its inclusion of only the most crucial equations, is an invaluable resource for students undertaking a course in statistics in any number of social science and behavioral disciplines-from education, business, communication, exercise science, psychology, sociology and more.

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.

In this book the author's theoretical framework builds on linguistic and psychological research, arguing that similar image-schematic notions should be grouped together into interconnected family hierarchies, with complexity increasing with regard to the addition of spatial and conceptual primitives. She introduces an image schema logic as a language to model image schemas, and she shows how the semantic content of image schemas can be used to improve computational concept invention. The book will be of value to researchers in artificial intelligence, cognitive science, psychology, and creativity.

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.

Now in its fifth, expanded edition, Using Sources Effectively, Fifth Edition targets the two most prominent problems in current research-paper writing: the increase in unintentional plagiarism and the ineffective use of research source material. Designed as a supplementary textbook for both undergraduate and graduate courses, this book will help every student who uses research in writing. Included in this edition are coverage of research strategies and source selection (Chapter 2), a chapter on quoting sources effectively (Chapter 4), and a chapter on sentence patterns (Chapter 10). APA and MLA citation styles have been updated throughout the text. To the student: This book was written to give you the knowledge and tools you can use to make your research-based writing more powerful and effective. Here are some examples: Mini-Research Projects at the end of each chapter to sharpen your research and evaluation skills A set of practical, useful rhetorical devices to help improve the clarity and impact of your writing Increased emphasis on synthesis writing-weaving source use into your own thinking-to give your writing more interest and persuasive power Instruction in close reading to help you better grasp what an author is discussing or arguing Strategies for organizing and positioning your sources to strengthen your central argument.

A new take on therapeutic mindfulness with specific applications to troubled and delinquent youth is the focus of this innovative text. It introduces Family Mode Deactivation Therapy (FMDT) and its core concepts and methodologies, differentiating it from other cognitive and mindfulness therapies for adolescents with problem behaviors and comorbid conditions. Step by step applications of FMDT from case conceptualization to assessment and treatment are featured, with detailed case studies demonstrating its effectiveness in treating mood disorders, aggressive behavior and trauma and guidelines for its use with abusive families and other complex cases. The book's depth of clinical detail and appendix of therapist tools make it especially practical. Included in the coverage: A comparison of MDT with other cognitive approaches. The empirical status of MDT. Mindfulness in MDT process, and in the treatment room. FMDT and sexual offender youth. MDT and mindfulness in the context of trauma. Treating the "untreatable": FMDT and challenging populations. While Treating Adolescents with Family-Based Mindfulness is immediately useful to practicing psychotherapists, it should also be of interest to other professionals with a role in adolescent health care, such as policymakers, social workers, supervisors, juvenile corrections and youth center personnel and students and researchers.

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.

Case study research is a versatile approach that allows for different data sources to be combined, with its main purpose being theory development. This book goes a step further by combining different case study research designs, informed by the authors' extensive teaching and research experience. It provides an accessible introduction to case study research, familiarizes readers with different archetypical and sequenced designs, and describes these designs and their components using both real and fictional examples. It provides thought-provoking exercises, and in doing so, prepares the reader to design their own case study in a way that suits the research objective. Written for an academic audience, this book is useful for students, their supervisors and professors, and ultimately any researcher who intends to use, or is already using, the case study approach.