Statistical Power Analysis For The Social And Behavioral Sciences

Author: Xiaofeng Steven Liu
Publisher: Routledge
ISBN: 1136464182
Size: 77.84 MB
Format: PDF, ePub
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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.

Statistical Power Analysis For The Behavioral Sciences

Author: Jacob Cohen
Publisher: Lawrence Erlbaum Associates
ISBN: 9780121790608
Size: 25.18 MB
Format: PDF, Mobi
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Statistical Power Analysis is a nontechnical guide to power analysis in research planning that provides users of applied statistics with the tools they need for more effective analysis. The Second Edition includes: * a chapter covering power analysis in set correlation and multivariate methods; * a chapter considering effect size, psychometric reliability, and the efficacy of "qualifying" dependent variables and; * expanded power and sample size tables for multiple regression/correlation.

Statistical Methods For The Social And Behavioural Sciences

Author: David B. Flora
Publisher: SAGE
ISBN: 1526421925
Size: 20.20 MB
Format: PDF, ePub, Docs
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Statistical methods in modern research increasingly entail developing, estimating and testing models for data. Rather than rigid methods of data analysis, the need today is for more flexible methods for modelling data. In this logical, easy-to-follow and exceptionally clear book, David Flora provides a comprehensive survey of the major statistical procedures currently used. His innovative model-based approach teaches you how to: Understand and choose the right statistical model to fit your data Match substantive theory and statistical models Apply statistical procedures hands-on, with example data analyses Develop and use graphs to understand data and fit models to data Work with statistical modeling principles using any software package Learn by applying, with input and output files for R, SAS, SPSS, and Mplus. Statistical Methods for the Social and Behavioural Sciences: A Model Based Approach is the essential guide for those looking to extend their understanding of the principles of statistics, and begin using the right statistical modeling method for their own data. It is particularly suited to second or advanced courses in statistical methods across the social and behavioural sciences.

The Sage Encyclopedia Of Educational Research Measurement And Evaluation

Author: Bruce B. Frey
Publisher: SAGE Publications
ISBN: 150632617X
Size: 60.37 MB
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In an era of curricular changes and experiments and high-stakes testing, educational measurement and evaluation is more important than ever. In addition to expected entries covering the basics of traditional theories and methods, other entries discuss important sociopolitical issues and trends influencing the future of that research and practice. Textbooks, handbooks, monographs and other publications focus on various aspects of educational research, measurement and evaluation, but to date, there exists no major reference guide for students new to the field. This comprehensive work fills that gap, covering traditional areas while pointing the way to future developments. Features: Nearly 700 signed entries are contained in an authoritative work spanning four volumes and available in choice of electronic and/or print formats. Although organized A-to-Z, front matter includes a Reader’s Guide grouping entries thematically to help students interested in a specific aspect of education research, measurement, and evaluation to more easily locate directly related entries. (For instance, sample themes include Data, Evaluation, Measurement Concepts & Issues, Research, Sociopolitical Issues, Standards.) Back matter includes a Chronology of the development of the field; a Resource Guide to classic books, journals, and associations; and a detailed Index. Entries conclude with References/Further Readings and Cross References to related entries. The Index, Reader’s Guide themes, and Cross References will combine to provide robust search-and-browse in the e-version.

Conducting Research In Online And Blended Learning Environments

Author: Charles D. Dziuban
Publisher: Routledge
ISBN: 1317804988
Size: 25.66 MB
Format: PDF, Mobi
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Conducting Research in Online and Blended Learning Environments examines various perspectives, issues, and methods for conducting research in online and blended learning environments. The book provides in-depth examinations of the perspectives and issues that anyone considering research in online or blended learning will find insightful as they plan their own inquiries. Grounded in educational research theory, this is invaluable to both the serious researcher as well as the occasional evaluator. Conducting Research in Online and Blended Learning Environments provides comprehensive, useful information on research paradigms, methodologies, and methods that should be considered in designing and conducting studies in this area. Examples of the most respected research in the field enhance each chapter’s presentation.

Bayesian Methods

Author: Jeff Gill
Publisher: CRC Press
ISBN: 1439862494
Size: 40.19 MB
Format: PDF
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An Update of the Most Popular Graduate-Level Introductions to Bayesian Statistics for Social Scientists Now that Bayesian modeling has become standard, MCMC is well understood and trusted, and computing power continues to increase, Bayesian Methods: A Social and Behavioral Sciences Approach, Third Edition focuses more on implementation details of the procedures and less on justifying procedures. The expanded examples reflect this updated approach. New to the Third Edition A chapter on Bayesian decision theory, covering Bayesian and frequentist decision theory as well as the connection of empirical Bayes with James–Stein estimation A chapter on the practical implementation of MCMC methods using the BUGS software Greatly expanded chapter on hierarchical models that shows how this area is well suited to the Bayesian paradigm Many new applications from a variety of social science disciplines Double the number of exercises, with 20 now in each chapter Updated BaM package in R, including new datasets, code, and procedures for calling BUGS packages from R This bestselling, highly praised text continues to be suitable for a range of courses, including an introductory course or a computing-centered course. It shows students in the social and behavioral sciences how to use Bayesian methods in practice, preparing them for sophisticated, real-world work in the field.

Statistical Power Analysis

Author: Kevin R. Murphy
Publisher: Routledge
ISBN: 1136910417
Size: 72.72 MB
Format: PDF, ePub, Docs
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First Published in 2009. Routledge is an imprint of Taylor & Francis, an informa company.

Statistical Test Theory For The Behavioral Sciences

Author: Dato N. M. de Gruijter
Publisher: CRC Press
ISBN: 9781584889595
Size: 56.17 MB
Format: PDF
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Since the development of the first intelligence test in the early 20th century, educational and psychological tests have become important measurement techniques to quantify human behavior. Focusing on this ubiquitous yet fruitful area of research, Statistical Test Theory for the Behavioral Sciences provides both a broad overview and a critical survey of assorted testing theories and models used in psychology, education, and other behavioral science fields. Following a logical progression from basic concepts to more advanced topics, the book first explains classical test theory, covering true score, measurement error, and reliability. It then presents generalizability theory, which provides a framework to deal with various aspects of test scores. In addition, the authors discuss the concept of validity in testing, offering a strategy for evidence-based validity. In the two chapters devoted to item response theory (IRT), the book explores item response models, such as the Rasch model, and applications, including computerized adaptive testing (CAT). The last chapter looks at some methods used to equate tests. Equipped with the essential material found in this book, advanced undergraduate and graduate students in the behavioral sciences as well as researchers involved in measurement and testing will gain valuable insight into the research methodologies and statistical data analyses of behavioral testing.

Modern Statistics For The Social And Behavioral Sciences

Author: Rand Wilcox
Publisher: CRC Press
ISBN: 149879680X
Size: 16.57 MB
Format: PDF, ePub, Mobi
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Requiring no prior training, Modern Statistics for the Social and Behavioral Sciences provides a two-semester, graduate-level introduction to basic statistical techniques that takes into account recent advances and insights that are typically ignored in an introductory course. Hundreds of journal articles make it clear that basic techniques, routinely taught and used, can perform poorly when dealing with skewed distributions, outliers, heteroscedasticity (unequal variances) and curvature. Methods for dealing with these concerns have been derived and can provide a deeper, more accurate and more nuanced understanding of data. A conceptual basis is provided for understanding when and why standard methods can have poor power and yield misleading measures of effect size. Modern techniques for dealing with known concerns are described and illustrated. Features: Presents an in-depth description of both classic and modern methods Explains and illustrates why recent advances can provide more power and a deeper understanding of data Provides numerous illustrations using the software R Includes an R package with over 1300 functions Includes a solution manual giving detailed answers to all of the exercises This second edition describes many recent advances relevant to basic techniques. For example, a vast array of new and improved methods is now available for dealing with regression, including substantially improved ANCOVA techniques. The coverage of multiple comparison procedures has been expanded and new ANOVA techniques are described. Rand Wilcox is a professor of psychology at the University of Southern California. He is the author of 13 other statistics books and the creator of the R package WRS. He currently serves as an associate editor for five statistics journals. He is a fellow of the Association for Psychological Science and an elected member of the International Statistical Institute.