This important new collection provides not only a comprehensive overview of how organizational interventions can improve health and well-being in the workplace - addressing its causes rather than the symptoms - but also the practical issues faced in their design, implementation and evaluation. Drawing on a range of case studies and empirical investigations, it is the first book to seriously examine each element of the intervention process, and to recognize the individual, group, leader and organizational factors that researchers should consider. The authors describe the various challenges to such collaborative processes, as well as the specific methods and tools that can be used in response. Each chapter offers practical, evidence-based guidance. Featuring a final section examining new directions and approaches in organizational intervention research, the book features contributions from some of the leading international researchers in the field. It will be essential reading for any researcher or practitioner interested in the practical issues involved in improving the organization, design and management of the contemporary workplace.

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.

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.

It is quite common to reflect on what startles you. In the most diverse social contexts and cultures, the inescapable physiology of the reflex both shapes the experience of startle and biases the social usage to which the reflex is put. This book describes the ways in which the reflex is experienced, culturally elaborated, and socially used, and offers explanations for both patterned commonalities found across cultures, and for the culture-typical differences which differing cultural systems engender.

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.

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.

Research Methodology is meant to provide a broad guideline to facilitate and steer the whole of a research activity in any discipline. With the ambit and amount of research increasing by the day, the need for Research Methodology is being widely appreciated. Against this backdrop, we notice the dearth of well-written books on the subject. A Guide to Research Methodology attempts a balance between the generic approach to research in any domain and the wide array of research methods which are to be used in carrying out different tasks in any research. Discussions on these research methods appropriate in various disciplines have focused on the research tasks, keeping in mind the fact that a single such task like a comparison among alternatives may involve several methods from seemingly distinct areas. Unique features of this volume, as will be evident to a discerning reader, include: A detailed discussion on problem areas for research in several domains An illustrative and ampliated list of research problems drawn from different disciplines which can be pursued by interested research workers A comprehensive delineation of Research Design supported by illustrations An elaborate engagement with models with a note on model uncertainty Focus on recent and emerging models, methods and techniques A novel treatment of data analysis where the nature of data and the objective(s) of analysis justify drawing upon a variety of techniques for analysis This book will serve the purpose of a pre-PhD or a Master-level course-work for students of any discipline with a basic knowledge of quantitative analysis. In fact, anyone aspiring to take up meaningful research work will find the content useful and interesting.

A Step-by-Step Guide to Qualitative Data Coding is a comprehensive qualitative data analysis guide. It is designed to help readers to systematically analyze qualitative data in a transparent and consistent manner, thus promoting the credibility of their findings. The book examines the art of coding data, categorizing codes, and synthesizing categories and themes. Using real data for demonstrations, it provides step-by-step instructions and illustrations for analyzing qualitative data. Some of the demonstrations include conducting manual coding using Microsoft Word and how to use qualitative data analysis software such as Dedoose, NVivo and QDA Miner Lite to analyze data. It also contains creative ways of presenting qualitative findings and provides practical examples. After reading this book, readers will be able to: Analyze qualitative data and present their findings Select an appropriate qualitative analysis tool Decide on the right qualitative coding and categorization strategies for their analysis Develop relationships among categories/themes Choose a suitable format for the presentation of the findings It is a great resource for qualitative research instructors and undergraduate and graduate students who want to gain skills in analyzing qualitative data or who plan to conduct a qualitative study. It is also useful for researchers and practitioners in the social and health sciences fields.

Highly recommended by the Journal of Official Statistics, The American Statistician, and other journals, Applied Survey Data Analysis, Second Edition provides an up-to-date overview of state-of-the-art approaches to the analysis of complex sample survey data. Building on the wealth of material on practical approaches to descriptive analysis and regression modeling from the first edition, this second edition expands the topics covered and presents more step-by-step examples of modern approaches to the analysis of survey data using the newest statistical software. Designed for readers working in a wide array of disciplines who use survey data in their work, this book continues to provide a useful framework for integrating more in-depth studies of the theory and methods of survey data analysis. An example-driven guide to the applied statistical analysis and interpretation of survey data, the second edition contains many new examples and practical exercises based on recent versions of real-world survey data sets. Although the authors continue to use Stata for most examples in the text, they also continue to offer SAS, SPSS, SUDAAN, R, WesVar, IVEware, and Mplus software code for replicating the examples on the book's updated website.

Applied Power Analysis for the Behavioral Sciences is a practical "how-to" guide to conducting statistical power analyses for psychology and related fields. The book provides a guide to conducting analyses that is appropriate for researchers and students, including those with limited quantitative backgrounds. With practical use in mind, the text provides detailed coverage of topics such as how to estimate expected effect sizes and power analyses for complex designs. The topical coverage of the text, an applied approach, in-depth coverage of popular statistical procedures, and a focus on conducting analyses using R make the text a unique contribution to the power literature. To facilitate application and usability, the text includes ready-to-use R code developed for the text. An accompanying R package called pwr2ppl (available at https://github.com/chrisaberson/pwr2ppl) provides tools for conducting power analyses across each topic covered in the text.

This book is designed to introduce professors and administrators in higher education to the philosophical, theoretical, and research support for using a constructivist perspective on learning to guide the reconstruction of undergraduate education. It presents an original framework for systematically linking educational philosophy and learning theories to their implications for teaching practice. In this volume, Innes summarizes the sources he found most useful in developing his own set of teaching principles and course development process, and makes an argument for a particular perspective on learning--transactional constructivism--which is consistent with the philosophy of John Dewey and supported by current theory and research in learning science. Transactional constructivism, a combined approach, builds on the strengths of two competing views: psychological constructivism and the sociocultural perspective. Reconstructing Undergraduate Education: Using Learning Science to Design Effective Courses: *overviews the philosophical and theoretical underpinnings of the teaching model that is the focus of the volume; *presents a summary of Dewey's educational philosophy and connects his work to current theory and research in learning science; *examines psychological constructivism, one of the basic positions within the range of learning theories that takes a constructivist perspective; *offers a case study example of a course designed and taught from this perspective; *reviews the sociocultural and the transactional constructivist perspectives; *explores the quality of dialogue and disciplinary discourse in the classroom--an issue that is critical to the success of models derived from a transactional constructivist perspective on learning; and *explores broader issues related to reform in higher education. This volume is a vital resource for all professionals involved in undergraduate education.

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.

Research Design and Statistical Analysis provides comprehensive coverage of the design principles and statistical concepts necessary to make sense of real data. The book s goal is to provide a strong conceptual foundation to enable readers to generalize concepts to new research situations. Emphasis is placed on the underlying logic and assumptions of the analysis and what it tells the researcher, the limitations of the analysis, and the consequences of violating assumptions. Sampling, design efficiency, and statistical models are emphasized throughout. As per APA recommendations, emphasis is also placed on data exploration, effect size measures, confidence intervals, and using power analyses to determine sample size. "Real-world" data sets are used to illustrate data exploration, analysis, and interpretation. The book offers a rare blend of the underlying statistical assumptions, the consequences of their violations, and practical advice on dealing with them.

Changes in the New Edition:

• Each section of the book concludes with a chapter that provides an integrated example of how to apply the concepts and procedures covered in the chapters of the section. In addition, the advantages and disadvantages of alternative designs are discussed.
• A new chapter (1) reviews the major steps in planning and executing a study, and the implications of those decisions for subsequent analyses and interpretations.
• A new chapter (13) compares experimental designs to reinforce the connection between design and analysis and to help readers achieve the most efficient research study.
• A new chapter (27) on common errors in data analysis and interpretation.
• Increased emphasis on power analyses to determine sample size using the G*Power 3 program.
• Many new data sets and problems.
• More examples of the use of SPSS (PASW) Version 17, although the analyses exemplified are readily carried out by any of the major statistical software packages.
• A companion website with the data used in the text and the exercises in SPSS and Excel formats; SPSS syntax files for performing analyses; extra material on logistic and multiple regression; technical notes that develop some of the formulas; and a solutions manual and the text figures and tables for instructors only.

Part 1 reviews research planning, data exploration, and basic concepts in statistics including sampling, hypothesis testing, measures of effect size, estimators, and confidence intervals. Part 2 presents between-subject designs. The statistical models underlying the analysis of variance for these designs are emphasized, along with the role of expected mean squares in estimating effects of variables, the interpretation of nteractions, and procedures for testing contrasts and controlling error rates. Part 3 focuses on repeated-measures designs and considers the advantages and disadvantages of different mixed designs. Part 4 presents detailed coverage of correlation and bivariate and multiple regression with emphasis on interpretation and common errors, and discusses the usefulness and limitations of these procedures as tools for prediction and for developing theory.

This is one of the few books with coverage sufficient for a 2-semester course sequence in experimental design and statistics as taught in psychology, education, and other behavioral, social, and health sciences. Incorporating the analyses of both experimental and observational data provides continuity of concepts and notation. Prerequisites include courses on basic research methods and statistics. The book is also an excellent resource for practicing researchers."

A daily glass of wine prolongs life-yet alcohol can cause life-threatening cancer. Some say raising the minimum wage will decrease inequality while others say it increases unemployment. Scientists once confidently claimed that hormone replacement therapy reduced the risk of heart disease but now they equally confidently claim it raises that risk. What should we make of this endless barrage of conflicting claims? Observation and Experiment is an introduction to causal inference by one of the field's leading scholars. An award-winning professor at Wharton, Paul Rosenbaum explains key concepts and methods through lively examples that make abstract principles accessible. He draws his examples from clinical medicine, economics, public health, epidemiology, clinical psychology, and psychiatry to explain how randomized control trials are conceived and designed, how they differ from observational studies, and what techniques are available to mitigate their bias. "Carefully and precisely written...reflecting superb statistical understanding, all communicated with the skill of a master teacher." -Stephen M. Stigler, author of The Seven Pillars of Statistical Wisdom "An excellent introduction...Well-written and thoughtful...from one of causal inference's noted experts." -Journal of the American Statistical Association "Rosenbaum is a gifted expositor...an outstanding introduction to the topic for anyone who is interested in understanding the basic ideas and approaches to causal inference." -Psychometrika "A very valuable contribution...Highly recommended." -International Statistical Review

Providing a practical, thorough understanding of how factor analysis works, Foundations of Factor Analysis, Second Edition discusses the assumptions underlying the equations and procedures of this method. It also explains the options in commercial computer programs for performing factor analysis and structural equation modeling. This long-awaited edition takes into account the various developments that have occurred since the publication of the original edition.

New to the Second Edition

• A new chapter on the multivariate normal distribution, its general properties, and the concept of maximum-likelihood estimation
• More complete coverage of descriptive factor analysis and doublet factor analysis
• A rewritten chapter on analytic oblique rotation that focuses on the gradient projection algorithm and its applications
• Discussions on the developments of factor score indeterminacy
• A revised chapter on confirmatory factor analysis that addresses philosophy of science issues, model specification and identification, parameter estimation, and algorithm derivation

Presenting the mathematics only as needed to understand the derivation of an equation or procedure, this textbook prepares students for later courses on structural equation modeling. It enables them to choose the proper factor analytic procedure, make modifications to the procedure, and produce new results.

This text teaches readers how to plan, conduct, and write a research project and select and interpret data through its integrated approach to quantitative research methods. Although not a statistics book, students learn to master which technique to use when and how to analyze and interpret results, making them better consumers of research. Organized around the steps of conducting a research project, this book is ideal for those who need to analyze journal articles. With teaching experience in various departments, the authors know how to address the research problems faced by behavioral and social sciences students. Independent sections and chapters can be read in any order allowing for flexibility in assigning topics. Adopters applaud the book's clarity and applied interdependent approach to research. The book emphasizes five research approaches: randomized experimental, quasi-experimental, comparative, associational, and descriptive. These five approaches lead to three kinds of research designs which lead to three groups of statistics with the same names. This consistent framework increases comprehension while avoiding confusion caused by inconsistent terminology. Numerous examples, diagrams, tables, key terms, key distinctions, summaries, applied problems, interpretation questions, and suggested readings further promote understanding. This extensively revised edition features: More examples from published research articles to help readers better understand the research process. New Research in the Real World boxes that highlight actual research projects from various disciplines. Defined key terms in the margins and interpretation questions that help readers review the material. More detailed explanations of key concepts including reliability, validity, estimation, ethical and bias concerns, data security and assumptions, power analysis , and multiple and logistic regression. New sections on mediation and moderation analysis to address the latest techniques. More coverage of quasi-experimental design and qualitative research to reflect changing practices. A new appendix on how to write about results using APA guidelines to help new researchers. Online resources available at www.routledge.com/9781138852976 that provide instructors with PowerPoints, test questions, critical thinking exercises, a conversion guide, and answers to all of the book's problems and questions. Students will find learning objectives, annotated links to further readings and key concepts, and key terms with links to definitions. Intended for graduate research methods or design or quantitative/experimental research methods courses in psychology, education, human development, family studies, and other behavioral, social, and health sciences, some exposure to statistics and research methods is recommended.

This practical, activity-based textbook from well-known psychology author Cara Flanagan covers everything you need to know for the research methods part of your A Level psychology course.The skills, knowledge and understanding needed to get to grips with this challenging part of the course are delived in an appealing magazine-style layout. Appropriate for all AS and A Level Psychology specifications (AQA, OCR, WJEC/Eduqas and Edexcel), this book is perfect for learning about research methods either as a stand-alone or integrated part of the course.

This book provides a comprehensive overview of research methods in the behavioral sciences, focusing primarily on the conceptual issues inherent in conducting research. It covers topics that are often omitted from other texts, including measurement issues, correlational research, qualitative research, and integrative literature reviews. The book also includes discussions of diversity issues as they related to behavioral science research. New to this edition are chapter boxes that focus on applied issues related to each chapter topic. Throughout the book, readable examples and informative tables and figures are provided. The authors also take a contemporary approach to topics such as research ethics, replication research, and data collection (including internet research).

Statistical Concepts-A Second Course presents the last 10 chapters from An Introduction to Statistical Concepts, Fourth Edition. Designed for second and upper-level statistics courses, this book highlights how statistics work and how best to utilize them to aid students in the analysis of their own data and the interpretation of research results. In this new edition, Hahs-Vaughn and Lomax discuss sensitivity, specificity, false positive and false negative errors. Coverage of effect sizes has been expanded upon and more organizational features (to summarize key concepts) have been included. A final chapter on mediation and moderation has been added for a more complete presentation of regression models. In addition to instructions and screen shots for using SPSS, new to this edition is annotated script for using R. This book acts as a clear and accessible instructional tool to help readers fully understand statistical concepts and how to apply them to data. It is an invaluable resource for students undertaking a course in statistics in any number of social science and behavioral science disciplines.

Psychology Research Methods: A Writing Intensive Approach provides instruction in critical concepts and processes in behavioral science research methods and skills in formulating and writing research papers. The book creates an experiential approach to learning, with chapters organized around the task of writing a complete APA-style research paper. The chapters consist of instructional text, excerpts from published research articles, and learning activities. The reading activities help students develop skills in reading scientific research, evaluating and analyzing scientific information, and assembling evidence to make a scientific argument. The writing activities help students to break down the process of writing a research paper into manageable and meaningful components. As students complete the chapter activities, they assemble their research paper. The book teaches research methods in a clinical context, inspired by the National Institute of Health's Science of Behavior Change Program. Students acquire knowledge about research methods as they read research articles about behavioral health disorders, including studies about their prevalence, causes, and treatment. Teaching research methods with a clinical focus helps students appreciate the value of psychological research. Psychology Research Methods: A Writing Intensive Approach provides instruction in critical concepts and processes in behavioral science research methods and skills in formulating and writing research papers. The book creates an experiential approach to learning, with chapters organized around the task of writing a complete APA-style research paper. The chapters consist of instructional text, excerpts from published research articles, and learning activities. The reading activities help students develop skills in reading scientific research, evaluating and analyzing scientific information, and assembling evidence to make a scientific argument. The writing activities help students to break down the process of writing a research paper into manageable and meaningful components. As students complete the chapter activities, they assemble their research paper. The book teaches research methods in a clinical context, inspired by the National Institute of Health's Science of Behavior Change Program. Students acquire knowledge about research methods as they read research articles about behavioral health disorders, including studies about their prevalence, causes, and treatment. Teaching research methods with a clinical focus helps students appreciate the value of psychological research. Psychology Research Methods: A Writing Intensive Approach provides instruction in critical concepts and processes in behavioral science research methods and skills in formulating and writing research papers. The book creates an experiential approach to learning, with chapters organized around the task of writing a complete APA-style research paper. The chapters consist of instructional text, excerpts from published research articles, and learning activities. The reading activities help students develop skills in reading scientific research, evaluating and analyzing scientific information, and assembling evidence to make a scientific argument. The writing activities help students to break down the process of writing a research paper into manageable and meaningful components. As students complete the chapter activities, they assemble their research paper. The book teaches research methods in a clinical context, inspired by the National Institute of Health's Science of Behavior Change Program. Students acquire knowledge about research methods as they read research articles about behavioral health disorders, including studies about their prevalence, causes, and treatment. Teaching research methods with a clinical focus helps students appreciate the value of psychological research.

Incorporating a hands-on pedagogical approach, Nonparametric Statistics for Social and Behavioral Sciences presents the concepts, principles, and methods used in performing many nonparametric procedures. It also demonstrates practical applications of the most common nonparametric procedures using IBM's SPSS software. This text is the only current nonparametric book written specifically for students in the behavioral and social sciences. Emphasizing sound research designs, appropriate statistical analyses, and accurate interpretations of results, the text: Explains a conceptual framework for each statistical procedure Presents examples of relevant research problems, associated research questions, and hypotheses that precede each procedure Details SPSS paths for conducting various analyses Discusses the interpretations of statistical results and conclusions of the research With minimal coverage of formulas, the book takes a nonmathematical approach to nonparametric data analysis procedures and shows students how they are used in research contexts. Each chapter includes examples, exercises, and SPSS screen shots illustrating steps of the statistical procedures and resulting output.

This guide reveals the best ways for students to analyse data and interpret results in SPSS. Georjeanna Wilson-Doenges's direct writing style, real sample data from her research methods class, integrated APA-style results, and detailed yet clear screenshots ensure that students feel confident using the programme. Her exciting revision not only reflects the latest updates to SPSS and APA guidelines but also includes new engaging step-by-step video tutorials.

Collecting and analyzing data on unemployment, inflation, and inequality help describe the complex world around us. When published by the government, such data are called official statistics. They are reported by the media, used by politicians to lend weight to their arguments, and by economic commentators to opine about the state of society. Despite such widescale use, explanations about how these measures are constructed are seldom provided for a non-technical reader. This Measuring Society book is a short, accessible guide to six topics: jobs, house prices, inequality, prices for goods and services, poverty, and deprivation. Each relates to concepts we use on a personal level to form an understanding of the society in which we live: We need a job, a place to live, and food to eat. Using data from the United States, we answer three basic questions: why, how, and for whom these statistics have been constructed. We add some context and flavor by discussing the historical background. This book provides the reader with a good grasp of these measures. Chaitra H. Nagaraja is an Associate Professor of Statistics at the Gabelli School of Business at Fordham University in New York. Her research interests include house price indices and inequality measurement. Prior to Fordham, Dr. Nagaraja was a researcher at the U.S. Census Bureau. While there, she worked on projects relating to the American Community Survey.