The use of multiple raters can improve the validity of conclusions made on self- (and other) reports of emotions, attitudes, goals, and self-perceptions of personality. Yet analyzing these ratings requires special psychometric models that take into account the specific nature of these data. From leading authorities, this book offers the first comprehensive introduction to structural equation modeling (SEM) of multiple rater data. Rather than taking a one-size-fits-all approach, the book shows how the choice of a model should be guided by measurement design and purpose. Practical recommendations are provided for selecting suitable measurement designs, raters, and psychometric models. Models for different combinations of rater types and for cross-sectional as well as longitudinal research designs are described step by step, with a strong emphasis on the substantive meaning of the latent variables in the models. User-friendly features include equation boxes, application boxes, and a companion website with Mplus and lavaan code for the book’s examples.
Since test items are the building blocks of any test, learning how to develop and validate test items has always been critical to the teaching-learning process. As they grow in importance and use, testing programs increasingly supplement the use of selected-response (multiple-choice) items with constructed-response formats. This trend is expected to continue. As a result, a new item writing book is needed, one that provides comprehensive coverage of both types of items and of the validity theory underlying them. This book is an outgrowth of the author’s previous book, Developing and Validating Multiple-Choice Test Items, 3e (Haladyna, 2004). That book achieved distinction as the leading source of guidance on creating and validating selected-response test items. Like its predecessor, the content of this new book is based on both an extensive review of the literature and on its author’s long experience in the testing field. It is very timely in this era of burgeoning testing programs, especially when these items are delivered in a computer-based environment. Key features include ... Comprehensive and Flexible – No other book so thoroughly covers the field of test item development and its various applications. Focus on Validity – Validity, the most important consideration in testing, is stressed throughout and is based on the Standards for Educational and Psychological Testing, currently under revision by AERA, APA, and NCME Illustrative Examples – The book presents various selected and constructed response formats and uses many examples to illustrate correct and incorrect ways of writing items. Strategies for training item writers and developing large numbers of items using algorithms and other item-generating methods are also presented. Based on Theory and Research – A comprehensive review and synthesis of existing research runs throughout the book and complements the expertise of its authors.
This book helps readers apply testing and measurement theories. Featuring 22 self-standing modules, instructors can pick and choose the ones that are most appropriate for their course. Each module features an overview of a measurement issue and a step-by-step application of that theory. Best practices provide recommendations for ensuring the appropriate application of the theory. Practical questions help students assess their understanding of the topic while the examples allow them to apply the material using real data. Two cases in each module depict typical dilemmas faced when applying measurement theory followed by Questions to Ponder to encourage critical examination of the issues noted in the cases. Each module contains exercises some of which require no computer access while others involve the use of SPSS to solve the problem. The book’s website houses the accompanying data sets and more. The book also features suggested readings, a glossary of the key terms, and a continuing exercise that incorporates many of the steps in the development of a measure of typical performance. Updated throughout to reflect recent changes in the field, the new edition also features: --A new co-author, Michael Zickar, who updated the advanced topics and added the new module on generalizability theory (Module 22). -Expanded coverage of reliability (Modules 5 & 6) and exploratory and confirmatory factor analysis (Modules 18 & 19) to help readers interpret results presented in journal articles. -Expanded Web Resources, Instructors will now find: suggested answers to the book’s questions and exercises; detailed worked solutions to the exercises; and PowerPoint slides. Students and instructors can access the SPSS data sets; additional exercises; the glossary; and website references that are helpful in understanding psychometric concepts. Part 1 provides an introduction to measurement theory and specs for scaling and testing and a review of statistics. Part 2 then progresses through practical issues related to text reliability, validation, meta-analysis and bias. Part 3 reviews practical issues related to text construction such as the development of measures of maximal performance, CTT item analysis, test scoring, developing measures of typical performance, and issues related to response styles and guessing. The book concludes with advanced topics such as multiple regression, exploratory and confirmatory factor analysis, item response theory (IRT), IRT applications including computer adaptive testing and differential item functioning, and generalizability theory. Ideal as a text for any psychometrics, testing and measurement, or multivariate statistics course taught in psychology, education, marketing and management, professional researchers in need of a quick refresher on applying measurement theory will also find this an invaluable reference.
This defining work will be valuable to readers and researchers in social sciences and humanities at all academic levels. As a teaching resource it will be useful to instructors and students alike and will become a standard reference source. Essential for general and academic collections." --CHOICE This Encyclopedia provides readers with authoritative essays on virtually all social science methods topics, quantitative and qualitative, by an international collection of experts. Organized alphabetically, the Encyclopedia of Social Science Research Methods covers research terms ranging from different methodological approaches to epistemological issues and specific statistical techniques. Written to be accessible to general readers, the Encyclopedia entries do not require advanced knowledge of mathematics or statistics to understand the purposes or basic principles of any of the methods. To accomplish this goal, there are two major types of entries: definitions consisting of a paragraph or two to provide a quick explanation of a methodological term; and topical treatments or essays that discuss the nature, history, applications, and implications of using a certain method, including suggested readings and references. Readers are directed to related topics via cross-referenced terms that appear in small capital letters. By assembling entries of varied origins and serving different research purposes, readers will be able to benefit from this immense source of methodological expertise in advancing their understanding of research. With three volumes and more than 900 signed entries, the Encyclopedia of Social Science Research Methods will be a critical addition to any social science library.
Guides readers through the quantitative data analysis process including contextualizing data within a research situation, connecting data to the appropriate statistical tests, and drawing valid conclusions Introduction to Quantitative Data Analysis in the Behavioral and Social Sciences presents a clear and accessible introduction to the basics of quantitative data analysis and focuses on how to use statistical tests as a key tool for analyzing research data. The book presents the entire data analysis process as a cyclical, multiphase process and addresses the processes of exploratory analysis, decision-making for performing parametric or nonparametric analysis, and practical significance determination. In addition, the author details how data analysis is used to reveal the underlying patterns and relationships between the variables and connects those trends to the data’s contextual situation. Filling the gap in quantitative data analysis literature, this book teaches the methods and thought processes behind data analysis, rather than how to perform the study itself or how to perform individual statistical tests. With a clear and conversational style, readers are provided with a better understanding of the overall structure and methodology behind performing a data analysis as well as the needed techniques to make informed, meaningful decisions during data analysis. The book features numerous data analysis examples in order to emphasize the decision and thought processes that are best followed, and self-contained sections throughout separate the statistical data analysis from the detailed discussion of the concepts allowing readers to reference a specific section of the book for immediate solutions to problems and/or applications. Introduction to Quantitative Data Analysis in the Behavioral and Social Sciences also features coverage of the following: • The overall methodology and research mind-set for how to approach quantitative data analysis and how to use statistics tests as part of research data analysis • A comprehensive understanding of the data, its connection to a research situation, and the most appropriate statistical tests for the data • Numerous data analysis problems and worked-out examples to illustrate the decision and thought processes that reveal underlying patterns and trends • Detailed examples of the main concepts to aid readers in gaining the needed skills to perform a full analysis of research problems • A conversational tone to effectively introduce readers to the basics of how to perform data analysis as well as make meaningful decisions during data analysis Introduction to Quantitative Data Analysis in the Behavioral and Social Sciences is an ideal textbook for upper-undergraduate and graduate-level research method courses in the behavioral and social sciences, statistics, and engineering. This book is also an appropriate reference for practitioners who require a review of quantitative research methods. Michael J. Albers, Ph.D., is Professor in the Department of English at East Carolina University. His research interests include information design with a focus on answering real-world questions, the presentation of complex information, and human–information interaction. Dr. Albers received his Ph.D. in Technical Communication and Rhetoric from Texas Tech University.
Debriefing is a major component of the job in many high-risk industries where errors can have considerable, often deadly consequences, including combat, surgery, and aviation. Although there exists considerable literature on debriefing, recent reviews of the literature suggest (a) shortcomings in the topics researched, (b) paucity of related theory, (c) limitations in the number of empirical studies, and (d) problems in research design. There are also recent suggestions that "there are surprisingly studies in the scholarly literature that show how to debrief, how to teach or learn to debrief, what methods of debriefing exists and how effective they are at achieving learning objectives and goals" Meta-analyses reveal substantial variations in research findings—e.g., on the use of video as a means of debriefing—that can be traced to the problems. This book redresses these problems in that it provides a detailed look at debriefing and assessment, the functions of different cognitive artifacts used, and a theoretical framework that accounts for the complexity of flying an aircraft and for the debriefing of the pilots’ experiences, especially under the high-stakes condition of their bi-annual evaluation for licensing purposes. The book provides detailed investigation of flight examiners’ methods to arrive at assessments of aviation pilot performance. It shows and theoretically models why there are good reasons for lower than desired inter-rater agreements. It offers detailed scenarios of how debriefing can be made to draw maximum benefit for pilot learning, that is, for the take-home messages that will make them better pilots. The theoretical framework includes objective factors that determine performance and the subjective experience pilots have while undergoing training and testing in flight simulators
Techniques in Hip Arthroscopy and Joint Preservation Surgery is a stunning visual guide to the latest developments in the field. Drs. Jon K. Sekiya, Marc Safran, and Anil S. Ranawat, and Michael Leunig provide a step-by-step, balanced approach—with contributions from an array of North American and international surgeons—to pre-operative planning, surgical technique, technical pearls, management of complications, and post-operative rehabilitation. Surgical videos online demonstrate techniques such as surgical hip dislocation for femoracetabular impingement and arthroscopic femoral osteoplasty so you can provide your patients with the best possible outcomes. - Access the fully searchable text online at www.expertconsult.com, along with a video library of surgical procedures. - Grasp the visual nuances of each technique through full-color surgical illustrations and intraoperative photographs. - Watch expert surgeons perform cutting edge procedures—such as complex therapeutic hip arthroscopy using a femoral distractor, arhroscopic synovectomy and treatment of synovial disorders, surgical hip dislocation for femoracetabular important, and arthroscopic femoral osteoplasty—online at www.expertconsult.com - Find information quickly and easily thanks to the consistent chapter format that includes technical pearls.
A BUSINESSWEEK BESTSELLER Bestselling Lean Six Sigma author Michael George provides the first pocket guide for deployers of Lean Six Sigma The Lean Six Sigma Pocket Toolbook blends Lean and Six Sigma tools and concepts, providing expert advice on how to determine which tool within a "family" is best for different purposes. Packed with detailed examples and step-bystep instructions, it's the ideal handy reference guide to help Green and Black Belts make the transition from the classroom to the field. Features brief summaries and examples of the 70 most important tools in Lean Six Sigma, such as "Pull," "Heijunka," and "Control Charts" Groups tools by purpose and usage Offers a quick, easy reference on using the DMAIC improvement cycle Provides comprehensive coverage in a compact, portable format
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