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This book describes the principles and techniques needed to analyze data that form a multiway contingency table. Wickens discusses the description of association in such data using log-linear and log-multiplicative models and defines how the presence of association is tested using hypotheses of independence and quasi-independence. The application of the procedures to real data is then detailed. This volume does not presuppose prior experience or knowledge of statistics beyond basic courses in fundamentals of probability and statistical inference. It serves as an ideal reference for professionals or as a textbook for graduate or advanced undergraduate students involved in statistics in the social sciences.
This book describes the principles and techniques needed to analyze data that form a multiway contingency table. Wickens discusses the description of association in such data using log-linear and log-multiplicative models and defines how the presence of association is tested using hypotheses of independence and quasi-independence. The application of the procedures to real data is then detailed. This volume does not presuppose prior experience or knowledge of statistics beyond basic courses in fundamentals of probability and statistical inference. It serves as an ideal reference for professionals or as a textbook for graduate or advanced undergraduate students involved in statistics in the social sciences.
This best-selling text is written for those who use, rather than develop statistical methods. Dr. Stevens focuses on a conceptual understanding of the material rather than on proving results. Helpful narrative and numerous examples enhance understanding and a chapter on matrix algebra serves as a review. Annotated printouts from SPSS and SAS indicate what the numbers mean and encourage interpretation of the results. In addition to demonstrating how to use these packages, the author stresses the importance of checking the data, assessing the assumptions, and ensuring adequate sample size by providing guidelines so that the results can be generalized. The book is noted for its extensive applied coverage of MANOVA, its emphasis on statistical power, and numerous exercises including answers to half. The new edition features: New chapters on Hierarchical Linear Modeling (Ch. 15) and Structural Equation Modeling (Ch. 16) New exercises that feature recent journal articles to demonstrate the actual use of multiple regression (Ch. 3), MANOVA (Ch. 5), and repeated measures (Ch. 13) A new appendix on the analysis of correlated observations (Ch. 6) Expanded discussions on obtaining non-orthogonal contrasts in repeated measures designs with SPSS and how to make the identification of cell ID easier in log linear analysis in 4 or 5 way designs Updated versions of SPSS (15.0) and SAS (8.0) are used throughout the text and introduced in chapter 1 A book website with data sets and more. Ideal for courses on multivariate statistics found in psychology, education, sociology, and business departments, the book also appeals to practicing researchers with little or no training in multivariate methods. Prerequisites include a course on factorial ANOVA and covariance. Working knowledge of matrix algebra is not assumed.
Agreement among raters is of great importance in many domains. For example, in medicine, diagnoses are often provided by more than one doctor to make sure the proposed treatment is optimal. In criminal trials, sentencing depends, among other things, on the complete agreement among the jurors. In observational studies, researchers increase reliability by examining discrepant ratings. This book is intended to help researchers statistically examine rater agreement by reviewing four different approaches to the technique. The first approach introduces readers to calculating coefficients that allow one to summarize agreements in a single score. The second approach involves estimating log-linear models that allow one to test specific hypotheses about the structure of a cross-classification of two or more raters' judgments. The third approach explores cross-classifications or raters' agreement for indicators of agreement or disagreement, and for indicators of such characteristics as trends. The fourth approach compares the correlation or covariation structures of variables that raters use to describe objects, behaviors, or individuals. These structures can be compared for two or more raters. All of these methods operate at the level of observed variables. This book is intended as a reference for researchers and practitioners who describe and evaluate objects and behavior in a number of fields, including the social and behavioral sciences, statistics, medicine, business, and education. It also serves as a useful text for graduate-level methods or assessment classes found in departments of psychology, education, epidemiology, biostatistics, public health, communication, advertising and marketing, and sociology. Exposure to regression analysis and log-linear modeling is helpful.
This book expertly guides the reader through all stages involved in undertaking quantitative psychological research, from accessing the relevant literature, through designing and conducting a study, analysing and interpreting data, and finally reporting the research. This third edition includes two new chapters - on preliminary checking of data and allowing for additional variables when comparing the means of different conditions - and expands on original topics such as choosing sample sizes and how to test for mediation effects. It also contains increased coverage of tests and further detail of techniques and terms which psychologists will meet when working with those in the medical professions. As the chapters focus on choosing appropriate statistical tests and how to interpret and report them (rather than the detailed calculations, which appear in appendices), the reader is able to gain an understanding of a test without being interrupted by the need to understand the complex mathematics behind it. In addition, for the first time, the book is accompanied by an online bank of multiple choice questions. The book helps readers to: Locate reports of relevant existing research Design research while adhering to ethical principles Identify various methods which can be used to ask questions or observe behaviour Choose appropriate samples Display and analyse findings numerically and graphically to test hypotheses Report psychological research in a variety of ways. As such, the book is suitable for psychology students and professionals at all levels, and is particularly useful to those working in Health and Clinical Psychology.
This new text consists of parts of Bornstein and Lamb’s Developmental Science, 6th edition along with new introductory material that as a whole provides a cutting edge and comprehensive overview of cognitive development. Each of the world-renowned contributors masterfully introduces the history and systems, methodologies, and measurement and analytic techniques used to understand human cognitive development. The relevance of cognition is illustrated through engaging applications. Each chapter reflects the current state of the field in cognitive development 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 cognitive developmental science and its relevance to everyday life. Students and instructors will also 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 cognitive 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 focuses on the field’s major substantive areas: neuroscience and genetics, physical and motor development, perception, and cognitive and language development. Intended for advanced undergraduate and/or beginning graduate courses on cognitive development taught in departments of psychology, human development and family studies, and education, researchers in these areas will appreciate this book’s cutting-edge coverage.
The goal of this book is to inform a broad readership about a variety of measures and estimators of effect sizes for research, their proper applications and interpretations, and their limitations. Its focus is on analyzing post-research results. The book provides an evenhanded account of controversial issues in the field, such as the role of significance testing. Consistent with the trend toward greater use of robust statistical methods, the book pays much attention to the statistical assumptions of the methods and to robust measures of effect size. Effect Sizes for Research discusses different effect sizes for a variety of kinds of variables, designs, circumstances, and purposes. It covers standardized differences between means, correlational measures, strength of association, and confidence intervals. The book clearly demonstrates how the choice of an appropriate measure might depend on such factors as whether variables are categorical, ordinal, or continuous; satisfying assumptions; the sampling method; and the source of variability in the population. It emphasizes a practical approach through: worked examples using real data; formulas and rationales for a variety of variables, designs, and purposes to help readers apply the material to their own data sets; software references for the more tedious calculations; and informative figures and tables, questions, and over 300 references. Intended as a resource for professionals, researchers, and advanced students in a variety of fields, this book is an excellent supplement for advanced courses in statistics in disciplines such as psychology, education, the social sciences, business, management, and medicine. A prerequisite of introductory statistics through factorial analysis of variance and chi-square is recommended.
Continuity and change have been major concerns of the social and behavioral sciences -- in the study of human development and in the study of processes that unfold in various ways across time. There has been a veritable explosion of techniques for studying change over time which have fundamentally changed how we need to think of and study change. Unfortunately, many of the old precepts and beliefs are still among us. The field of methodology for the study of change is itself ready to change. Recently, there have been many analytic and conceptual developments questioning our cherished beliefs about the study of change. As such, how are individuals to think about issues and correctly analyze change? The chapters in this volume address these issues. Divided into two sections, this book deals with designs that analyze change in multiple subjects, and with change in single subjects and an interacting system. Papers presented in this volume are accessible to scientists who are not methodologists. The character of the papers are more like primers than basic treatises on methodology, written for other methodologists. It is time that people stop thinking in rigid ways about how to study change and be introduced to a range of many possibilities. Change, stability, order and chaos are elusive concepts. The pursuit of the laws of change must be approached in as flexible and creative a fashion as possible. This book should help to lead the way.
A companion volume to Family Observational Coding Systems, this book moves from the triad to the dyad and provides a showcase for significant developments in the coding of intimate couple interactions. The hope is that this book will contribute to the broadening and deepening of the field by disseminating information both about the coding systems that have been developed, as well as the conceptual and methodological issues involved in couple observational research. The first three chapters present overviews of conceptual and methodological issues in the study of couple processes. The remaining chapters describe contributions to the field by 16 teams of researchers. Each chapter provides information about the conceptual underpinnings and structure of the coding system developed by the authors and evidence for its psychometric properties. Couple Observational Coding Systems will be of interest to researchers studying couple interactions as well as clinicians who work with couples.