SPSS
Discovering Statistics Using IBM SPSS Statistics by
Unrivaled in the way it makes the teaching of statistics compelling and accessible to even the most anxious of students, the only statistics textbook you and your students will ever need just got better! Andy Field's comprehensive and bestselling Discovering Statistics Using SPSS 4th Edition takes students from introductory statistical concepts through very advanced concepts, incorporating SPSS throughout. The Fourth Edition focuses on providing essential content updates, better accessibility to key features, more instructor resources, and more content specific to select disciplines. It also incorporates powerful new digital developments on the textbook's companion website.
ISBN: 9781446249185Publication Date: 2013-01-24
MPLUS
- Mplus: Statistical Analysis With Latent Variables (User's Guide) - Version 5 byPublication Date: November 2007
Power Analysis
Applied Power Analysis for the Behavioral Sciences by
This practical guide to conducting statistical power analyses was written for students and researchers with limited quantitative backgrounds. The book focuses on conducting power analyzes using SPSS and details calculations and comments on what goes where and how it got there.
ISBN: 9781848728356Publication Date: 2010-02-09
Power Analysis for Experimental Research by
Power analysis is an essential tool for determining whether a statistically significant result can be expected in a scientific experiment prior to the experiment being performed. This comprehensive, accessible book provides practicing researchers with step-by-step instructions for conducting power/sample size analyses, assuming only basic prior knowledge of summary statistics and normal distribution. It contains a unified approach to statistical power analysis, with numerous easy-to-use tables that make further calculations or statistical expertise unnecessary.
ISBN: 9780521024563Publication Date: 2006-03-09
Determining Sample Size by
A researcher's decision about the sample to draw in a study may have an enormous impact on the results, and it rests on numerous statistical and practical considerations that can be difficult to juggle. Computer programs help, but no single software package exists that allows researchers to determine sample size across all statistical procedures. This pocket guide shows social work students, educators, and researchers how to prevent some of the mistakes that would result from a wrong sample size decision by describing and critiquing four main approaches to determining sample size. In concise, example-rich chapters, Dattalo covers sample-size determination using power analysis, confidence intervals, computer-intensive strategies, and ethical or cost considerations, as well as techniques for advanced and emerging statistical strategies such as structural equation modeling, multilevel analysis, repeated measures MANOVA and repeated measures ANOVA. He also offers strategies for mitigating pressures to increase sample size when doing so may not be feasible. Whether as an introduction to the process for students or as a refresher for experienced researchers, Determining Sample Size is a perfect overview of a crucial but often overlooked step in empirical social work research.
ISBN: 9780195315493Publication Date: 2008-01-11
Statistical Power Analysis for the Behavioral Sciences by
This non-technical guide to power analysis in research planning provides users of applied statistics with the tools they need for more effective analysis. Expanded and updated, the book uses the same approach and organization as the previous edition, but includes a chapter covering power analysis in set correlation and multivariate methods, a chapter considering the effect size, psychometric reliability and the efficacy of qualifying dependent variables, and expanded power and sample size tables for multiple regression/correlation.
ISBN: 9780805802832Publication Date: 1988-07-01
HLM6
- Hierarchical Linear and Nonlinear Modeling by This book describes version 6 of the HLM computer program for multilevel analysis by Raudenbush, Bryk, & Congdon. It includes chapters on the conceptual and statistical background as well as chapters on how to work with the program.ISBN: 9780894980541Publication Date: 2004
Lisrel 8
- LISREL 8 byISBN: 9780894980336Publication Date: 1993-01-01
R
Comparing Groups by
<b>A hands-on guide to using R to carry out key statistical practices in</b> <b>educational and behavioral sciences research</b> <p>Computing has become an essential part of the day-to-day practice of statistical work, broadening the types of questions that can now be addressed by research scientists applying newly derived data analytic techniques. <i>Comparing Groups: Randomization and Bootstrap Methods Using R</i> emphasizes the direct link between scientific research questions and data analysis. Rather than relying on mathematical calculations, this book focus on conceptual explanations and the use of statistical computing in an effort to guide readers through the integration of design, statistical methodology, and computation to answer specific research questions regarding group differences.</p> <p>Utilizing the widely-used, freely accessible R software, the authors introduce a modern approach to promote methods that provide a more complete understanding of statistical concepts. Following an introduction to R, each chapter is driven by a research question, and empirical data analysis is used to provide answers to that question. These examples are data-driven inquiries that promote interaction between statistical methods and ideas and computer application. Computer code and output are interwoven in the book to illustrate exactly how each analysis is carried out and how output is interpreted. Additional topical coverage includes:</p> <ul type="disc"> <li>Data exploration of one variable and multivariate data</li> <li>Comparing two groups and many groups</li> <li>Permutation tests, randomization tests, and the independent samples t-Test</li> <li>Bootstrap tests and bootstrap intervals</li> <li>Interval estimates and effect sizes</li> </ul> <p>Throughout the book, the authors incorporate data from real-world research studies as well aschapter problems that provide a platform to perform data analyses. A related Web site features a complete collection of the book′s datasets along with the accompanying codebooks and the R script files and commands, allowing readers to reproduce the presented output and plots.</p> <p><i>Comparing Groups: Randomization and Bootstrap Methods Using R</i> is an excellent book for upper-undergraduate and graduate level courses on statistical methods, particularlyin the educational and behavioral sciences. The book also serves as a valuable resource for researchers who need a practical guide to modern data analytic and computational methods.</p>
ISBN: 9780470621691Publication Date: 2011-06-15
Advanced Theory of Statistics
- Advanced Theory of Statistics Vol 1-3 byPublication Date: 1967