Statistical methods for categorical data analysis, Powers, Daniel Xie, Yu
Автор: Azen, Razia (the University Of Wisconsin- Milwaukee, Usa) Walker, Cindy M. (the University Of Wisconsin- Milwaukee, Usa) Название: Categorical data analysis for the behavioral and social sciences ISBN: 0367352761 ISBN-13(EAN): 9780367352769 Издательство: Taylor&Francis Рейтинг: Цена: 14086.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Featuring a practical approach with numerous examples, the second edition of Categorical Data Analysis for the Behavioral and Social Sciences focuses on helping the reader develop a conceptual understanding of categorical methods, making it a much more accessible text than others on the market. The authors cover common categorical analysis methods and emphasize specific research questions that can be addressed by each analytic procedure, including how to obtain results using SPSS, SAS, and R, so that readers are able to address the research questions they wish to answer.Each chapter begins with a "Look Ahead" section to highlight key content. This is followed by an in-depth focus and explanation of the relationship between the initial research question, the use of software to perform the analyses, and how to interpret the output substantively. Included at the end of each chapter are a range of software examples and questions to test knowledge.New to the second edition:The addition of R syntax for all analyses and an update of SPSS and SAS syntax.The addition of a new chapter on GLMMs.Clarification of concepts and ideas that graduate students found confusing, including revised problems at the end of the chapters.Written for those without an extensive mathematical background, this book is ideal for a graduate course in categorical data analysis taught in departments of psychology, educational psychology, human development and family studies, sociology, public health, and business. Researchers in these disciplines interested in applying these procedures will also appreciate this book’s accessible approach.
Автор: Erling B. Andersen Название: The Statistical Analysis of Categorical Data ISBN: 364278819X ISBN-13(EAN): 9783642788192 Издательство: Springer Рейтинг: Цена: 15372.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The aim of this book is to give an up to date account of the most commonly uses statisti- cal models for categorical data. In many cases, the data sets are those data sets, which were not included in the examples of the book, although they at one point in time were regarded as potential can- didates for an example.
Автор: Tang, Wan (tulane University, New Orleans, La) He, Hua (tulane University) Tu, Xin M. (university Of California-san Diego) Название: Applied categorical and count data analysis ISBN: 0367568276 ISBN-13(EAN): 9780367568276 Издательство: Taylor&Francis Рейтинг: Цена: 12248.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This second edition explains how to perform the statistical analysis of discrete data, including categorical and count outcomes. It covers classic concepts and popular topics, such as logistic regression models, along with modern areas including models for zero-modified count outcomes.
Автор: Nussbaum E Michael Название: Categorical and Nonparametric Data Analysis ISBN: 1138787825 ISBN-13(EAN): 9781138787827 Издательство: Taylor&Francis Рейтинг: Цена: 12248.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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.
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: J.D. Jobson Название: Applied Multivariate Data Analysis ISBN: 1461269474 ISBN-13(EAN): 9781461269472 Издательство: Springer Рейтинг: Цена: 13974.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: A Second Course in Statistics The past decade has seen a tremendous increase in the use of statistical data analysis and in the availability of both computers and statistical software.
Автор: Guogen Shan Название: Exact Statistical Inference for Categorical Data ISBN: 0081006810 ISBN-13(EAN): 9780081006818 Издательство: Elsevier Science Рейтинг: Цена: 8757.00 р. Наличие на складе: Поставка под заказ.
Описание:
Exact Statistical Inference for Categorical Data discusses the way asymptotic approaches have been often used in practice to make statistical inference. This book introduces both conditional and unconditional exact approaches for the data in 2 by 2, or 2 by k contingency tables, and is an ideal reference for users who are interested in having the convenience of applying asymptotic approaches, with less computational time. In addition to the existing conditional exact inference, some efficient, unconditional exact approaches could be used in data analysis to improve the performance of the testing procedure.
Demonstrates how exact inference can be used to analyze data in 2 by 2 tables
Discusses the analysis of data in 2 by k tables using exact inference
Explains how exact inference can be used in genetics
Автор: Brajendra C. Sutradhar Название: Longitudinal Categorical Data Analysis ISBN: 1493953206 ISBN-13(EAN): 9781493953202 Издательство: Springer Рейтинг: Цена: 13275.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This is the first book in longitudinal categorical data analysis with parametric correlation models developed based on dynamic relationships among repeated categorical responses.
Автор: Y. Sakamoto Название: Categorical Data Analysis by AIC ISBN: 0792314298 ISBN-13(EAN): 9780792314295 Издательство: Springer Рейтинг: Цена: 13275.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Presents a practical approach to categorical data analysis based on the Akaike Information Criterion (AIC) and the Akaike Bayesian Information Criterion (ABIC). Topics covered include variable selection for categorical data, Bayesian binary regression and nonparametric density estimator.
Автор: James K. Lindsey Название: The Analysis of Categorical Data Using GLIM ISBN: 0387970290 ISBN-13(EAN): 9780387970295 Издательство: Springer Рейтинг: Цена: 16070.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Besides their previous statistics courses, these students have had an introductory course in computer programming (FORTRAN, Pascal, or C) and courses in calculus and linear algebra, so that they may not be typical students of sociology.
Автор: Tam?s Rudas Название: Lectures on Categorical Data Analysis ISBN: 1493992597 ISBN-13(EAN): 9781493992591 Издательство: Springer Рейтинг: Цена: 9083.00 р. Наличие на складе: Поставка под заказ.
Описание: This book offers a relatively self-contained presentation of the fundamental results in categorical data analysis, which plays a central role among the statistical techniques applied in the social, political and behavioral sciences, as well as in marketing and medical and biological research. The methods applied are mainly aimed at understanding the structure of associations among variables and the effects of other variables on these interactions. A great advantage of studying categorical data analysis is that many concepts in statistics become transparent when discussed in a categorical data context, and, in many places, the book takes this opportunity to comment on general principles and methods in statistics, addressing not only the “how” but also the “why.” Assuming minimal background in calculus, linear algebra, probability theory and statistics, the book is designed to be used in upper-undergraduate and graduate-level courses in the field and in more general statistical methodology courses, as well as a self-study resource for researchers and professionals. The book covers such key issues as: higher order interactions among categorical variables; the use of the delta-method to correctly determine asymptotic standard errors for complex quantities reported in surveys; the fundamentals of the main theories of causal analysis based on observational data; the usefulness of the odds ratio as a measure of association; and a detailed discussion of log-linear models, including graphical models. The book contains over 200 problems, many of which may also be used as starting points for undergraduate research projects. The material can be used by students toward a variety of goals, depending on the degree of theory or application desired.
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