Download or read book Contingency Table Analysis written by Maria Kateri and published by Springer. This book was released on 2014-05-17 with total page 315 pages. Available in PDF, EPUB and Kindle. Book excerpt: Contingency tables arise in diverse fields, including life sciences, education, social and political sciences, notably market research and opinion surveys. Their analysis plays an essential role in gaining insight into structures of the quantities under consideration and in supporting decision making. Combining both theory and applications, this book presents models and methods for the analysis of two- and multidimensional-contingency tables. An excellent reference for advanced undergraduates, graduate students, and practitioners in statistics as well as biosciences, social sciences, education, and economics, the work may also be used as a textbook for a course on categorical data analysis. Prerequisites include basic background on statistical inference and knowledge of statistical software packages.

Download or read book The Analysis of Contingency Tables Second Edition written by Brian S. Everitt and published by CRC Press. This book was released on 1992-02-01 with total page 178 pages. Available in PDF, EPUB and Kindle. Book excerpt: Much of the data collected in medicine and the social sciences is categorical, for example, sex, marital status, blood group, whether a smoker or not and so on, rather than interval-scaled. Frequently the researcher collecting such data is interested in the relationships or associations between pairs, or between a set of such categorical variables; often the data is displayed in the form of a contingency table for example, smoker versus non-smoker against death from lung cancer or death from some other cause. This text gives a comprehensive account of the analysis of such tables, written at a level suitable for the applied researcher. The first edition of "The Analysis of Contingency Tables" arose from Professor A.E. Maxwell's earlier text, "Analysing Qualitative Data". In this new edition, more material is included that those methods which have developed over the last decade or so, for example, logistic regression models for tables with ordered categories and for response variables with more than two categories. A brief account is given of the increasingly important technique, correspondence analysis. The methods of analysis described in this book should be relevant to research workers and graduate students dealing with data from surveys, particularly in the area of psychiatry, social sciences and psychology.

Download or read book Tests in Contingency Tables as Regression Tests written by Stanislav Anatolyev and published by . This book was released on 2006 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Applied researchers often use tests based on contingency tables in preliminary data analysis and diagnostic testing. We show that many of such tests may be alternatively implemented by testing for coefficient restrictions in linear regression systems (as a rule, employing the Wald test). This unifies the theories of regression analysis and contingency tables, sheds more light on intuitive contents of contingency table tests, and provides a more convenient and familiar tool for practitioners.

Download or read book Multiple Regressions from Contingency Tables written by Mingche M. Li and published by . This book was released on 1975 with total page 44 pages. Available in PDF, EPUB and Kindle. Book excerpt: In Section II and Section III, we use a simple example of black homeownership to show that identical results are obtained whether we run a regression with over 23,000 individual household records or with a modest contingency table having eight cells, available from the published census report. Moreover, we show that the interaction effect between independent variables can be estimated from either form of data. We then discuss two strategies for dealing with the situation in which the sample joint distribution between some pair of variables in a set of contingency tables is missing, and provide a se:1.sitivity test of the estimated coefficients under different assumptions about the missing joint distribution. Section IV focuses on the estimate obtained under the assumption of independence between the two variables, which is equivalent to assuming that we have absolutely no information about the missing joint distribution; whereas, Section V suggests that, if we take advantage of any knowledge about the joint distribution of its parent population, however remotely related to the sample, the error in the prediction of the missing sample joint distribution is greatly reduced. As extensions to the use of contingency tables, we also present a conditional logit estimate (Section VI), which is a weighted least squares regression, as well as a maximum likelihood estimate (Section VII), which is a modified multiple regression in the analysis of dichotomous variables. These two approaches are especially suitable for the estimation of relationships involving qualitative variables. Both belong to the class of consistent asymptotically normal estimators. Using a numerical example, we compare the estimates obtained using the three alternative methods.

Download or read book The Analysis of Contingency Tables written by Brian Everitt and published by Chapman and Hall/CRC. This book was released on 1977-06 with total page 148 pages. Available in PDF, EPUB and Kindle. Book excerpt: For several years now my book Analysing Qualitative Data has been in need of revision. Since it was first published in 1961, and in part perhaps because of it, a great deal of new and interesting work on the analysis of contingency tables has been published. Mr. Brian Everitt kindly undertook to do the revision but, when he came to review recent literature, it became apparent that a mere renovation of the original text would not be enough; the amount of new work was not only extensive but also made obsolete many of the older methods. In consequence, and with the agreement of the publishers, it was decided that the revised version should in effect be a new book. That it is so is not strikingly evident in the first two chapters of the present text which, by way of introduction, cover old ground. Thereafter, the increased scope of new methods becomes abundantly apparent. This can be illustrated by a single example. When the Iiterature up to 1961 was reviewed the big disappointment was the paucity and inadequacy of methods then available for the analysis of multidimensional tables, and they are the rule rather than the exception in research work in the social sciences.

Download or read book Contingency Tables and Regression written by Daniel Thorburn and published by . This book was released on 1985 with total page 44 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Introductory Statistics written by Openstax and published by . This book was released on 2022-03-23 with total page 914 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introductory Statistics follows scope and sequence requirements of a one-semester introduction to statistics course and is geared toward students majoring in fields other than math or engineering. The text assumes some knowledge of intermediate algebra and focuses on statistics application over theory. Introductory Statistics includes innovative practical applications that make the text relevant and accessible, as well as collaborative exercises, technology integration problems, and statistics labs. Senior Contributing Authors Barbara Illowsky, De Anza College Susan Dean, De Anza College Contributing Authors Daniel Birmajer, Nazareth College Bryan Blount, Kentucky Wesleyan College Sheri Boyd, Rollins College Matthew Einsohn, Prescott College James Helmreich, Marist College Lynette Kenyon, Collin County Community College Sheldon Lee, Viterbo University Jeff Taub, Maine Maritime Academy

Download or read book An Introduction to Categorical Data Analysis written by Alan Agresti and published by John Wiley & Sons. This book was released on 2018-10-11 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: A valuable new edition of a standard reference The use of statistical methods for categorical data has increased dramatically, particularly for applications in the biomedical and social sciences. An Introduction to Categorical Data Analysis, Third Edition summarizes these methods and shows readers how to use them using software. Readers will find a unified generalized linear models approach that connects logistic regression and loglinear models for discrete data with normal regression for continuous data. Adding to the value in the new edition is: • Illustrations of the use of R software to perform all the analyses in the book • A new chapter on alternative methods for categorical data, including smoothing and regularization methods (such as the lasso), classification methods such as linear discriminant analysis and classification trees, and cluster analysis • New sections in many chapters introducing the Bayesian approach for the methods of that chapter • More than 70 analyses of data sets to illustrate application of the methods, and about 200 exercises, many containing other data sets • An appendix showing how to use SAS, Stata, and SPSS, and an appendix with short solutions to most odd-numbered exercises Written in an applied, nontechnical style, this book illustrates the methods using a wide variety of real data, including medical clinical trials, environmental questions, drug use by teenagers, horseshoe crab mating, basketball shooting, correlates of happiness, and much more. An Introduction to Categorical Data Analysis, Third Edition is an invaluable tool for statisticians and biostatisticians as well as methodologists in the social and behavioral sciences, medicine and public health, marketing, education, and the biological and agricultural sciences.

Download or read book Applied Categorical and Count Data Analysis written by Wan Tang and published by CRC Press. This book was released on 2023-04-06 with total page 1699 pages. Available in PDF, EPUB and Kindle. Book excerpt: Developed from the authors’ graduate-level biostatistics course, Applied Categorical and Count Data Analysis, Second Edition explains how to perform the statistical analysis of discrete data, including categorical and count outcomes. The authors have been teaching categorical data analysis courses at the University of Rochester and Tulane University for more than a decade. This book embodies their decade-long experience and insight in teaching and applying statistical models for categorical and count data. The authors describe the basic ideas underlying each concept, model, and approach to give readers a good grasp of the fundamentals of the methodology without relying on rigorous mathematical arguments. The second edition covers classic concepts and popular topics, such as contingency tables, logistic regression models, and Poisson regression models, along with modern areas that include models for zero-modified count outcomes, parametric and semiparametric longitudinal data analysis, reliability analysis, and methods for dealing with missing values. As in the first edition, R, SAS, SPSS, and Stata programming codes are provided for all the examples, enabling readers to immediately experiment with the data in the examples and even adapt or extend the codes to fit data from their own studies. Designed for a one-semester course for graduate and senior undergraduate students in biostatistics, this self-contained text is also suitable as a self-learning guide for biomedical and psychosocial researchers. It will help readers analyze data with discrete variables in a wide range of biomedical and psychosocial research fields. Features: Describes the basic ideas underlying each concept and model Includes R, SAS, SPSS and Stata programming codes for all the examples Features significantly expanded Chapters 4, 5, and 8 (Chapters 4-6, and 9 in the second edition Expands discussion for subtle issues in longitudinal and clustered data analysis such as time varying covariates and comparison of generalized linear mixed-effect models with GEE

Download or read book Introduction to Statistical Machine Learning written by Masashi Sugiyama and published by Morgan Kaufmann. This book was released on 2015-10-31 with total page 535 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine learning allows computers to learn and discern patterns without actually being programmed. When Statistical techniques and machine learning are combined together they are a powerful tool for analysing various kinds of data in many computer science/engineering areas including, image processing, speech processing, natural language processing, robot control, as well as in fundamental sciences such as biology, medicine, astronomy, physics, and materials. Introduction to Statistical Machine Learning provides a general introduction to machine learning that covers a wide range of topics concisely and will help you bridge the gap between theory and practice. Part I discusses the fundamental concepts of statistics and probability that are used in describing machine learning algorithms. Part II and Part III explain the two major approaches of machine learning techniques; generative methods and discriminative methods. While Part III provides an in-depth look at advanced topics that play essential roles in making machine learning algorithms more useful in practice. The accompanying MATLAB/Octave programs provide you with the necessary practical skills needed to accomplish a wide range of data analysis tasks. - Provides the necessary background material to understand machine learning such as statistics, probability, linear algebra, and calculus - Complete coverage of the generative approach to statistical pattern recognition and the discriminative approach to statistical machine learning - Includes MATLAB/Octave programs so that readers can test the algorithms numerically and acquire both mathematical and practical skills in a wide range of data analysis tasks - Discusses a wide range of applications in machine learning and statistics and provides examples drawn from image processing, speech processing, natural language processing, robot control, as well as biology, medicine, astronomy, physics, and materials

Download or read book Least Squares Regression from Contingency Tables written by Mingche M. Li and published by . This book was released on 1976 with total page 40 pages. Available in PDF, EPUB and Kindle. Book excerpt: The 1970 Census provides a great deal of cross-tabulated information from which ordinary least squares (OLS) regression may be estimated. This paper shows that identical product moment matrices (X'X and X'y) can be generated either from individual observations or from summary statistics in the form of contingency tables. It is relatively easy to empoloye regression on readily available census tables to derive the same results that would be obtained if individual records could be secured.

Download or read book Statistical Analysis of Contingency Tables written by Morten Fagerland and published by CRC Press. This book was released on 2017-07-28 with total page 593 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical Analysis of Contingency Tables is an invaluable tool for statistical inference in contingency tables. It covers effect size estimation, confidence intervals, and hypothesis tests for the binomial and the multinomial distributions, unpaired and paired 2x2 tables, rxc tables, ordered rx2 and 2xc tables, paired cxc tables, and stratified tables. For each type of table, key concepts are introduced, and a wide range of intervals and tests, including recent and unpublished methods and developments, are presented and evaluated. Topics such as diagnostic accuracy, inter-rater reliability, and missing data are also covered. The presentation is concise and easily accessible for readers with diverse professional backgrounds, with the mathematical details kept to a minimum. For more information, including a sample chapter and software, please visit the authors' website.

Download or read book Statistical Persuasion written by Robert W. Pearson and published by SAGE Publications. This book was released on 2010-01-20 with total page 425 pages. Available in PDF, EPUB and Kindle. Book excerpt: "A number of my students commended the readability of the book....It is truly one of a kind in the most excellent way." -Elsie Szecsy, Arizona State University This textbook focuses attention on the conceptual understanding of statistics, the signposts of (in)appropriate research design and quality measurement, the selection of the right statistical tools under different conditions, and the presentation of substantive and technical results. Key Features Illustrates statistical and graphical procedures in SPSS and Excel through step-by-step instructions for the analysis of real-world examples and data problems in education, crime, government performance, and program evaluation Clearly demonstrates the importance of sound research designs and measurement as well as appropriate statistical procedures Shows how to make persuasive as well as principled statistical arguments and presentations to nonacademic audiences Embeds statistical analysis within a political framework, thus alerting students to the temptation to distort data and its interpretation, the limits of dispassionate analysis, and the conditions under which sound analysis can inform decisions Instructors interested in this title can learn more about Robert Pearson and his book by viewing his YouTube video. Accompanied by robust ancillaries The Password-Protected Instructor Teaching Site offers sample syllabi; an instructor′s manual; PowerPoint lecture slides, test questions and answer keys for each chapter and a final comprehensive examination, solution sets to lab exercises, and handouts for students. The Student Study Site offers a student workbook that includes exercises, essay assignments, and sample data sets. Video lectures concerning key concepts are also available on YouTube.

Download or read book Regression for Categorical Data written by Gerhard Tutz and published by Cambridge University Press. This book was released on 2011-11-21 with total page 573 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces basic and advanced concepts of categorical regression with a focus on the structuring constituents of regression, including regularization techniques to structure predictors. In addition to standard methods such as the logit and probit model and extensions to multivariate settings, the author presents more recent developments in flexible and high-dimensional regression, which allow weakening of assumptions on the structuring of the predictor and yield fits that are closer to the data. A generalized linear model is used as a unifying framework whenever possible in particular parametric models that are treated within this framework. Many topics not normally included in books on categorical data analysis are treated here, such as nonparametric regression; selection of predictors by regularized estimation procedures; ternative models like the hurdle model and zero-inflated regression models for count data; and non-standard tree-based ensemble methods. The book is accompanied by an R package that contains data sets and code for all the examples.

Download or read book Odds Ratios in the Analysis of Contingency Tables written by Tamás Rudas and published by SAGE. This book was released on 1998 with total page 92 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this volume the author shows how odds ratios can be used as a framework for understanding log-linear models. The book moves from paradigmatic 2x2 case to more complicated cases. The author also carefully defines the odds ratio.

Download or read book Several Numerical Procedures in Regression and Parametric Estimation in Contingency Tables written by John Carl Keegel and published by . This book was released on 1975 with total page 128 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Learning Statistics with R written by Daniel Navarro and published by Lulu.com. This book was released on 2013-01-13 with total page 617 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Learning Statistics with R" covers the contents of an introductory statistics class, as typically taught to undergraduate psychology students, focusing on the use of the R statistical software and adopting a light, conversational style throughout. The book discusses how to get started in R, and gives an introduction to data manipulation and writing scripts. From a statistical perspective, the book discusses descriptive statistics and graphing first, followed by chapters on probability theory, sampling and estimation, and null hypothesis testing. After introducing the theory, the book covers the analysis of contingency tables, t-tests, ANOVAs and regression. Bayesian statistics are covered at the end of the book. For more information (and the opportunity to check the book out before you buy!) visit http://ua.edu.au/ccs/teaching/lsr or http://learningstatisticswithr.com