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Statistical power analysis with missing data, Davey, Adam Savla, Jyoti


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Автор: Davey, Adam Savla, Jyoti
Название:  Statistical power analysis with missing data
ISBN: 9780805863697
Издательство: Taylor&Francis
Классификация:




ISBN-10: 0805863699
Обложка/Формат: Hardcover
Страницы: 384
Вес: 0.63 кг.
Дата издания: 20.08.2009
Язык: English
Размер: 237 x 164 x 26
Читательская аудитория: Professional & vocational
Подзаголовок: A structural equation modeling approach
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Поставляется из: Европейский союз
Описание:

Statistical power analysis has revolutionized the ways in which we conduct and evaluate research. Similar developments in the statistical analysis of incomplete (missing) data are gaining more widespread applications. This volume brings statistical power and incomplete data together under a common framework, in a way that is readily accessible to those with only an introductory familiarity with structural equation modeling. It answers many practical questions such as:

  • How missing data affects the statistical power in a study
  • How much power is likely with different amounts and types of missing data
  • How to increase the power of a design in the presence of missing data, and
  • How to identify the most powerful design in the presence of missing data.

Points of Reflection encourage readers to stop and test their understanding of the material. Try Me sections test ones ability to apply the material. Troubleshooting Tips help to prevent commonly encountered problems. Exercises reinforce content and Additional Readings provide sources for delving more deeply into selected topics. Numerous examples demonstrate the books application to a variety of disciplines. Each issue is accompanied by its potential strengths and shortcomings and examples using a variety of software packages (SAS, SPSS, Stata, LISREL, AMOS, and MPlus). Syntax is provided using a single software program to promote continuity but in each case, parallel syntax using the other packages is presented in appendixes. Routines, data sets, syntax files, and links to student versions of software packages are found at www.psypress.com/davey. The worked examples in Part 2 also provide results from a wider set of estimated models. These tables, and accompanying syntax, can be used to estimate statistical power or required sample size for similar problems under a wide range of conditions.

Class-tested at Temple, Virginia Tech, and Miami University of Ohio, this brief text is an ideal supplement for graduate courses in applied statistics, statistics II, intermediate or advanced statistics, experimental design, structural equation modeling, power analysis, and research methods taught in departments of psychology, human development, education, sociology, nursing, social work, gerontology and other social and health sciences. The books applied approach will also appeal to researchers in these areas. Sections covering Fundamentals, Applications, and Extensions are designed to take readers from first steps to mastery.




The Elements of Statistical Learning

Автор: Trevor Hastie; Robert Tibshirani; Jerome Friedman
Название: The Elements of Statistical Learning
ISBN: 0387848576 ISBN-13(EAN): 9780387848570
Издательство: Springer
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Цена: 10480.00 р.
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Описание: This major new edition features many topics not covered in the original, including graphical models, random forests, and ensemble methods. As before, it covers the conceptual framework for statistical data in our rapidly expanding computerized world.

Time Series Analysis

Автор: Hamilton, James
Название: Time Series Analysis
ISBN: 0691042896 ISBN-13(EAN): 9780691042893
Издательство: Wiley
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Цена: 11088.00 р.
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Описание: A graduate-level text which describes the recent dramatic changes that have taken place in the way that researchers analyze economic and financial time series. It explores such important innovations as vector regression, nonlinear time series models and the generalized methods of moments.

How Many Subjects?: Statistical Power Analysis in Research

Автор: Kraemer Helena C., Blasey Christine M.
Название: How Many Subjects?: Statistical Power Analysis in Research
ISBN: 1483319547 ISBN-13(EAN): 9781483319544
Издательство: Sage Publications
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Цена: 5859.00 р.
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Описание: Addressing a common question posed by researchers, this book introduces readers to power analysis and sample size determination and clearly illustrates why sample sizes need to be sufficiently large to give good power properties and low error rates.

Statistical Analysis with Missing Data, Third Edit ion

Автор: Little
Название: Statistical Analysis with Missing Data, Third Edit ion
ISBN: 0470526793 ISBN-13(EAN): 9780470526798
Издательство: Wiley
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Цена: 12664.00 р.
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Описание: Reflecting new application topics, Statistical Analysis with Missing Data offers a thoroughly up-to-date, reorganized survey of current methodology for handling missing data problems. The third edition reviews historical approaches to the subject and describe rigorous yet simple methods for multivariate analysis with missing values.

Introduction to Probability, Second Edition

Автор: Joseph K. Blitzstein, Jessica Hwang
Название: Introduction to Probability, Second Edition
ISBN: 1138369918 ISBN-13(EAN): 9781138369917
Издательство: Taylor&Francis
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Цена: 11176.00 р.
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Описание: Assumes one-semester of calculus. "Stories" make distributions (Normal, Binomial, Poisson that are widely-used in statistics) easier to remember, understand. Many books write down formulas without explaining clearly why these particular distributions are important or how they are all connected.

Handbook of Statistical Analysis and Data Mining Applications, 2 ed.

Автор: Robert Nisbet , Gary Miner, Ken Yale
Название: Handbook of Statistical Analysis and Data Mining Applications, 2 ed.
ISBN: 0124166326 ISBN-13(EAN): 9780124166325
Издательство: Elsevier Science
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Цена: 13304.00 р.
Наличие на складе: Поставка под заказ.

Описание:

Handbook of Statistical Analysis and Data Mining Applications, Second Edition, is a comprehensive professional reference book that guides business analysts, scientists, engineers and researchers, both academic and industrial, through all stages of data analysis, model building and implementation. The handbook helps users discern technical and business problems, understand the strengths and weaknesses of modern data mining algorithms and employ the right statistical methods for practical application.

This book is an ideal reference for users who want to address massive and complex datasets with novel statistical approaches and be able to objectively evaluate analyses and solutions. It has clear, intuitive explanations of the principles and tools for solving problems using modern analytic techniques and discusses their application to real problems in ways accessible and beneficial to practitioners across several areas--from science and engineering, to medicine, academia and commerce.

  • Includes input by practitioners for practitioners
  • Includes tutorials in numerous fields of study that provide step-by-step instruction on how to use supplied tools to build models
  • Contains practical advice from successful real-world implementations
  • Brings together, in a single resource, all the information a beginner needs to understand the tools and issues in data mining to build successful data mining solutions
  • Features clear, intuitive explanations of novel analytical tools and techniques, and their practical applications
The Analysis of Biological Data

Автор: Michael C. Whitlock, Dolph Schluter
Название: The Analysis of Biological Data
ISBN: 1319325343 ISBN-13(EAN): 9781319325343
Издательство: Macmillan Learning
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Цена: 13858.00 р.
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Описание: The evolution of a classicThe new 12th edition of Introduction to Genetic Analysis takes this cornerstone textbook to the next level.

Statistical power analysis for the behavioral sciences

Автор: J. Cohen
Название: Statistical power analysis for the behavioral sciences
ISBN: 0805802835 ISBN-13(EAN): 9780805802832
Издательство: Taylor&Francis
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Цена: 22202.00 р.
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Описание: This non-technical guide to power analysis in research planning in the behavioural sciences, provides users of applied statistics with the tools needed for more effective analysis. This edition includes a new chapter covering power analysis in set correlations and multivariate methods.

Using R and RStudio for Data Management, Statistical Analysis, and Graphics, Second Edition

Автор: Nicholas J. Horton , Ken Kleinman
Название: Using R and RStudio for Data Management, Statistical Analysis, and Graphics, Second Edition
ISBN: 1482237369 ISBN-13(EAN): 9781482237368
Издательство: Taylor&Francis
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Цена: 11789.00 р.
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Описание:

Improve Your Analytical Skills

Incorporating the latest R packages as well as new case studies and applications, Using R and RStudio for Data Management, Statistical Analysis, and Graphics, Second Edition covers the aspects of R most often used by statistical analysts. New users of R will find the book's simple approach easy to understand while more sophisticated users will appreciate the invaluable source of task-oriented information.

New to the Second Edition

  • The use of RStudio, which increases the productivity of R users and helps users avoid error-prone cut-and-paste workflows
  • New chapter of case studies illustrating examples of useful data management tasks, reading complex files, making and annotating maps, "scraping" data from the web, mining text files, and generating dynamic graphics
  • New chapter on special topics that describes key features, such as processing by group, and explores important areas of statistics, including Bayesian methods, propensity scores, and bootstrapping
  • New chapter on simulation that includes examples of data generated from complex models and distributions
  • A detailed discussion of the philosophy and use of the knitr and markdown packages for R
  • New packages that extend the functionality of R and facilitate sophisticated analyses
  • Reorganized and enhanced chapters on data input and output, data management, statistical and mathematical functions, programming, high-level graphics plots, and the customization of plots

Easily Find Your Desired Task

Conveniently organized by short, clear descriptive entries, this edition continues to show users how to easily perform an analytical task in R. Users can quickly find and implement the material they need through the extensive indexing, cross-referencing, and worked examples in the text. Datasets and code are available for download on a supplementary website.

Statistical and econometric methods for transportation data analysis

Автор: Washington, Simon Mannering, Fred (university Of S
Название: Statistical and econometric methods for transportation data analysis
ISBN: 0367199025 ISBN-13(EAN): 9780367199029
Издательство: Taylor&Francis
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Цена: 17609.00 р.
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Описание: Describing tools commonly used in the field, this textbook provides an understanding of a broad range of analytical tools required to solve transportation problems. It includes a wide breadth of examples and case studies in various aspects of transportation planning, engineering, safety, and economics.

Bayesian Data Analysis, Third Edition

Автор: Gelman
Название: Bayesian Data Analysis, Third Edition
ISBN: 1439840954 ISBN-13(EAN): 9781439840955
Издательство: Taylor&Francis
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Цена: 11088.00 р.
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Описание: Winner of the 2016 De Groot Prize from the International Society for Bayesian Analysis Now in its third edition, this classic book is widely considered the leading text on Bayesian methods, lauded for its accessible, practical approach to analyzing data and solving research problems. Bayesian Data Analysis, Third Edition continues to take an applied approach to analysis using up-to-date Bayesian methods. The authors—all leaders in the statistics community—introduce basic concepts from a data-analytic perspective before presenting advanced methods. Throughout the text, numerous worked examples drawn from real applications and research emphasize the use of Bayesian inference in practice. New to the Third Edition Four new chapters on nonparametric modeling Coverage of weakly informative priors and boundary-avoiding priors Updated discussion of cross-validation and predictive information criteria Improved convergence monitoring and effective sample size calculations for iterative simulation Presentations of Hamiltonian Monte Carlo, variational Bayes, and expectation propagation New and revised software code The book can be used in three different ways. For undergraduate students, it introduces Bayesian inference starting from first principles. For graduate students, the text presents effective current approaches to Bayesian modeling and computation in statistics and related fields. For researchers, it provides an assortment of Bayesian methods in applied statistics. Additional materials, including data sets used in the examples, solutions to selected exercises, and software instructions, are available on the book’s web page.


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