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The classic edition of What If There Were No Significance Tests? highlights current statistical inference practices. Four areas are featured as essential for making inferences: sound judgment, meaningful research questions, relevant design, and assessing fit in multiple ways. Other options (data visualization, replication or meta-analysis), other features (mediation, moderation, multiple levels or classes), and other approaches (Bayesian analysis, simulation, data mining, qualitative inquiry) are also suggested. The Classic Edition’s new Introduction demonstrates the ongoing relevance of the topic and the charge to move away from an exclusive focus on NHST, along with new methods to help make significance testing more accessible to a wider body of researchers to improve our ability to make more accurate statistical inferences. Part 1 presents an overview of significance testing issues. The next part discusses the debate in which significance testing should be rejected or retained. The third part outlines various methods that may supplement significance testing procedures. Part 4 discusses Bayesian approaches and methods and the use of confidence intervals versus significance tests. The book concludes with philosophy of science perspectives. Rather than providing definitive prescriptions, the chapters are largely suggestive of general issues, concerns, and application guidelines. The editors allow readers to choose the best way to conduct hypothesis testing in their respective fields. For anyone doing research in the social sciences, this book is bound to become "must" reading. Ideal for use as a supplement for graduate courses in statistics or quantitative analysis taught in psychology, education, business, nursing, medicine, and the social sciences, the book also benefits independent researchers in the behavioral and social sciences and those who teach statistics.
The purpose of this book is not only to revisit the “significance test controversy,”but also to provide a conceptually sounder alternative. As such, it presents a Bayesian framework for a new approach to analyzing and interpreting experimental data. It also prepares students and researchers for reporting on experimental results. Normative aspects: The main views of statistical tests are revisited and the philosophies of Fisher, Neyman-Pearson and Jeffrey are discussed in detail. Descriptive aspects: The misuses of Null Hypothesis Significance Tests are reconsidered in light of Jeffreys’ Bayesian conceptions concerning the role of statistical inference in experimental investigations. Prescriptive aspects: The current effect size and confidence interval reporting practices are presented and seriously questioned. Methodological aspects are carefully discussed and fiducial Bayesian methods are proposed as a more suitable alternative for reporting on experimental results. In closing, basic routine procedures regarding the means and their generalization to the most common ANOVA applications are presented and illustrated. All the calculations discussed can be easily carried out using the freeware LePAC package.
Psychology is of interest to academics from many fields, as well as to the thousands of academic and clinical psychologists and general public who can't help but be interested in learning more about why humans think and behave as they do. This award-winning twelve-volume reference covers every aspect of the ever-fascinating discipline of psychology and represents the most current knowledge in the field. This ten-year revision now covers discoveries based in neuroscience, clinical psychology's new interest in evidence-based practice and mindfulness, and new findings in social, developmental, and forensic psychology.
How do you bridge the gap between what you learned in your statistics course and the questions you want to answer in your real-world research? Oriented towards distinct questions in a "How do I?" or "When should I?" format, Your Statistical Consultant is the equivalent of the expert colleague down the hall who fields questions about describing, explaining, and making recommendations regarding thorny or confusing statistical issues. The book serves as a compendium of statistical knowledge, both theoretical and applied, that addresses the questions most frequently asked by students, researchers and instructors. Written to be responsive to a wide range of inquiries and levels of expertise, the book is flexibly organized so readers can either read it sequentially or turn directly to the sections that correspond to their concerns.
This text helps readers understand how to collect, manage, evaluate, and analyze data. It also provides guidelines for the presentation of analysis, especially for nonacademic audiences without training in statistical analysis. These guidelines help ensure that statistics and graphical displays tell the story that analysts want to convey while protecting their analysis from methodological criticism. Author Robert Pearson focuses attention on the conceptual understanding of statistics, while referring (sparingly) to specific formulas when they help reveal a conceptual point about the statistics. Key Features · Combines a concern for the design, collection, measurement, and the management of data with its analysis and presentation · Provides examples and data concerning real world problems in education, crime, government performance, and other policy arenas · Clearly demonstrates the steps used to generate the appropriate statistics and graphs in Excel and SPSS and then provides exercises to replicate and elaborate on these examples This book and its supporting materials are ideally suited for graduate students in professional degree programs in public policy, education, social work, criminology, urban planning, and related schools as well as advanced undergraduates in these fields. The book's explanations, descriptions, illustrations, and step-by-step exercises create the skills and knowledge required of a policy analyst, advisor, consultant or the elected or appointed public official or nonprofit officer who wants to be better able to interpret and evaluate others' applied social research. Its data sets, solutions sets, instructors' manual, lecture slides, and student workbook provide instructors with a complete and fully integrated instructional package.
This new text contains parts of Bornstein and Lamb’s Developmental Science, 6th edition, along with new introductory material, providing a cutting edge and comprehensive overview of social and personality development. Each of the world-renowned contributors masterfully introduces the history and systems, methodologies, and measurement and analytic techniques used to understand the area of human development under review. The relevance of the field is illustrated through engaging applications. Each chapter reflects the current state of knowledge and features an introduction, an overview of the field, a chapter summary, and numerous classical and contemporary references. As a whole, this highly anticipated text illuminates substantive phenomena in social and personality developmental science and its relevance to everyday life. Students and instructors will appreciate the book’s online resources. For each chapter, the website features: chapter outlines; a student reading guide; a glossary of key terms and concepts; and suggested readings with hotlinks to journal articles. Only instructors are granted access to the test bank with multiple-choice, short-answer, and essay questions; PowerPoints with all of the text’s figures and tables; and suggestions for classroom discussion/assignments. The book opens with an introduction to social and personality development as well as an overview of developmental science in general—its history and theory, the cultural orientation to thinking about human development, and the manner in which empirical research is designed, conducted, and analyzed. Part 2 examines personality and social development within the context of the various relationships and situations in which developing individuals function and by which they are shaped. The book concludes with an engaging look at applied developmental psychology in action through a current examination of children and the law. Ways in which developmental thinking and research affect and are affected by practice and social policy are emphasized. Intended for advanced undergraduate and/or graduate level courses on social and personality development taught in departments of psychology, human development, and education, researchers in these areas will also appreciate this book’s cutting-edge coverage.
Examining the major approaches to hypothesis testing and model selection, this book blends statistical theory with recommendations for practice, illustrated with real-world social science examples. It systematically compares classical (frequentist) and Bayesian approaches, showing how they are applied, exploring ways to reconcile the differences between them, and evaluating key controversies and criticisms. The book also addresses the role of hypothesis testing in the evaluation of theories, the relationship between hypothesis tests and confidence intervals, and the role of prior knowledge in Bayesian estimation and Bayesian hypothesis testing. Two easily calculated alternatives to standard hypothesis tests are discussed in depth: the Akaike information criterion (AIC) and Bayesian information criterion (BIC). The companion website ([ital]www.guilford.com/weakliem-materials[/ital]) supplies data and syntax files for the book's examples.
Trout advances scientific realism as a behavioural science. He introduces measured realism which characterizes a kind of uneven but indisputable theoretical progress in the social and psychological sciences.
This new book introduces a new generation to the important insights of Paul Meehl. In addition to selected papers from the classic reader, Psychodiagnosis, this book features new material selected from Meehl's most influential writings. The resulting collection is a tour de force illustrating quantitative analysis of life science problems, an examination of the inadequacy of some methods of analysis, and a review of the application of taxometrics. A Paul Meehl Reader is organized into five content areas: theory building and appraisal - how we discover and test the true causal relations of psychological constructs; specific etiology - an examination of genetic, behavioral, and environmental etiology in psychopathology; diagnosis and prediction - a review of the appropriate use of base rates; taxometrics - a look at Meehl's development of the method he invented; thinking effectively about psychological questions - a critique of correlation research and the power of quantitative thinking in psychology. The Reader features section introductions to orient the reader and provide a context and structure for Paul Meehl's work. The section on diagnosis and prediction features problem sets with solutions to guide the reader through practical applications of the principles described. Accompanying downloadable resources contain footage from Paul Meehl's engaging seminar on clinical versus statistical prediction. This book appeals to advanced students and professionals in psychology, sociology, law, education, human development, and philosophy.