The Essence of Multivariate Thinking, Harlow, Lisa L.

Автор: Harlow, Lisa L.
Название: The Essence of Multivariate Thinking
ISBN: 0415873711 ISBN-13(EAN): 9780415873710
Издательство: Taylor&Francis
Цена: 178640 T
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Автор: Harlow, Lisa L.
Название: The Essence of Multivariate Thinking
ISBN: 0415873711 ISBN-13(EAN): 9780415873710
Издательство: Taylor&Francis
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Цена: 178640.00 T
Наличие на складе: Нет в наличии.

Автор: Harlow, Lisa L.
Название: The Essence of Multivariate Thinking
ISBN: 0367219727 ISBN-13(EAN): 9780367219727
Издательство: Taylor&Francis
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Цена: 56130.00 T
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Автор: Kimmo Vehkalahti , Brian S. Everitt
Название: Multivariate Analysis for the Behavioral Sciences, Second Edition
ISBN: 0815385153 ISBN-13(EAN): 9780815385158
Издательство: Taylor&Francis
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Цена: 86760.00 T
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Описание: Multivariate Analysis for the Behavioral Sciences, Second Edition is designed to show how a variety of statistical methods can be used to analyse data collected by psychologists and other behavioral scientists.

Автор: Arthur, Jr.
Название: Conducting Meta-Analysis Using SAS
ISBN: 0805838090 ISBN-13(EAN): 9780805838091
Издательство: Taylor&Francis
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Цена: 40820.00 T
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Описание: Designed to teach the reader about meta-analysis and show them how to conduct one using SAS. Its focus is more applied and practical than theoretical and will include additional programming codes and examples. Web site to house program code and sample ou

Автор: Manly Bryan F.J.
Название: Multivariate Statistical Methods
ISBN: 1498728960 ISBN-13(EAN): 9781498728966
Издательство: Taylor&Francis
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Цена: 58170.00 T
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Описание:

Multivariate Statistical Methods: A Primer provides an introductory overview of multivariate methods without getting too deep into the mathematical details. This fourth edition is a revised and updated version of this bestselling introductory textbook. It retains the clear and concise style of the previous editions of the book and focuses on examples from biological and environmental sciences. The major update with this edition is that R code has been included for each of the analyses described, although in practice any standard statistical package can be used.

The original idea with this book still applies. This was to make it as short as possible and enable readers to begin using multivariate methods in an intelligent manner. With updated information on multivariate analyses, new references, and R code included, this book continues to provide a timely introduction to useful tools for multivariate statistical analysis.

Автор: Harlow
Название: What If There Were No Significance Tests?
ISBN: 1138892475 ISBN-13(EAN): 9781138892477
Издательство: Taylor&Francis
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Цена: 67360.00 T
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Описание: 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.

Автор: Byrne
Название: Structural Equation Modeling With AMOS
ISBN: 1138797030 ISBN-13(EAN): 9781138797031
Издательство: Taylor&Francis
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Цена: 59190.00 T
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Описание: This bestselling text provides a practical guide to structural equation modeling (SEM) using the Amos Graphical approach. Using clear, everyday language, the text is ideal for those with little to no exposure to either SEM or Amos.

Автор: Pituch
Название: Applied Multivariate Statistics for the Social Sciences
ISBN: 0415836654 ISBN-13(EAN): 9780415836654
Издательство: Taylor&Francis
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Цена: 234790.00 T
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Описание: Noted for its breadth and depth of coverage of multivariate statistics and its emphasis on power, this classic text focuses on a conceptual understanding of the material rather than on proving results. Numerous examples, along with use of SAS and SPSS, indicate what the numbers mean and how to interpret the results.

Автор: Nussbaum E Michael
Название: Categorical and Nonparametric Data Analysis
ISBN: 1138787825 ISBN-13(EAN): 9781138787827
Издательство: Taylor&Francis
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Цена: 81650.00 T
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Описание: Featuring in-depth coverage of categorical and nonparametric statistics, this book provides a conceptual framework for choosing the most appropriate type of test in various research scenarios. Class tested at the University of Nevada, the book's clear explanations of the underlying assumptions, computer simulations, and Exploring the Concept boxes help reduce reader anxiety. Problems inspired by actual studies provide meaningful illustrations of the techniques. The underlying assumptions of each test and the factors that impact validity and statistical power are reviewed so readers can explain their assumptions and how tests work in future publications. Numerous examples from psychology, education, and other social sciences demonstrate varied applications of the material. Basic statistics and probability are reviewed for those who need a refresher. Mathematical derivations are placed in optional appendices for those interested in this detailed coverage. Highlights include the following: Unique coverage of categorical and nonparametric statistics better prepares readers to select the best technique for their particular research project; however, some chapters can be omitted entirely if preferred. Step-by-step examples of each test help readers see how the material is applied in a variety of disciplines.  Although the book can be used with any program, examples of how to use the tests in SPSS and Excel foster conceptual understanding. Exploring the Concept boxes integrated throughout prompt students to review key material and draw links between the concepts to deepen understanding.  Problems in each chapter help readers test their understanding of the material.  Emphasis on selecting tests that maximize power helps readers avoid "marginally" significant results.  Website (www.routledge.com/9781138787827) features datasets for the book's examples and problems, and for the instructor, PowerPoint slides, sample syllabi, answers to the even-numbered problems, and Excel data sets for lecture purposes. Intended for individual or combined graduate or advanced undergraduate courses in categorical and nonparametric data analysis, cross-classified data analysis, advanced statistics and/or quantitative techniques taught in psychology, education, human development, sociology, political science, and other social and life sciences, the book also appeals to researchers in these disciplines. The nonparametric chapters can be deleted if preferred. Prerequisites include knowledge of t tests and ANOVA.

Автор: Matthias von Davier; Claus H. Carstensen
Название: Multivariate and Mixture Distribution Rasch Models
ISBN: 1441921966 ISBN-13(EAN): 9781441921963
Издательство: Springer
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Цена: 121110.00 T
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Описание: This book examines extensions of the Rasch model, one of the most researched and applied models in educational research and social science. They cover topics ranging from general model extensions to applications in fields as diverse as cognition, personality, organizational and sports psychology, and health sciences and education.

Автор: Dugard
Название: Approaching Multivariate Analysis, 2nd Edition
ISBN: 0415645913 ISBN-13(EAN): 9780415645911
Издательство: Taylor&Francis
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Цена: 57150.00 T
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Описание: This book gets students started, and prepares them to approach more comprehensive treatments with confidence. It`s an ideal text for psychology students, medical students and for any students or academics in disciplines that use multivariate methods.

Автор: Newsom
Название: Longitudinal Data Analysis
ISBN: 0415874149 ISBN-13(EAN): 9780415874144
Издательство: Taylor&Francis
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Цена: 148010.00 T
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Описание:

This book provides accessible treatment to state-of-the-art approaches to analyzing longitudinal studies. Comprehensive coverage of the most popular analysis tools allows readers to pick and choose the techniques that best fit their research. The analyses are illustrated with examples from major longitudinal data sets including practical information about their content and design. Illustrations from popular software packages offer tips on how to interpret the results. Each chapter features suggested readings for additional study and a list of articles that further illustrate how to implement the analysis and report the results. Syntax examples for several software packages for each of the chapter examples are provided at www.psypress.com/longitudinal-data-analysis.

Although many of the examples address health or social science questions related to aging, readers from other disciplines will find the analyses relevant to their work. In addition to demonstrating statistical analysis of longitudinal data, the book shows how to interpret and analyze the results within the context of the research design. The methods covered in this book are applicable to a range of applied problems including short- to long-term longitudinal studies using a range of sample sizes.

The book provides non-technical, practical introductions to the concepts and issues relevant to longitudinal analysis. Topics include use of publicly available data sets, weighting and adjusting for complex sampling designs with longitudinal studies, missing data and attrition, measurement issues related to longitudinal research, the use of ANOVA and regression for average change over time, mediation analysis, growth curve models, basic and advanced structural equation models, and survival analysis.

An ideal supplement for graduate level courses on data analysis and/or longitudinal modeling taught in psychology, gerontology, public health, human development, family studies, medicine, sociology, social work, and other behavioral, social, and health sciences, this multidisciplinary book will also appeal to researchers in these fields.