The Analysis of Contingency Tables


Book Description

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.




The Analysis of Contingency Tables


Book Description

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;




Contingency Table Analysis


Book Description

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.




Statistical Analysis of Contingency Tables


Book Description

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.




Odds Ratios in the Analysis of Contingency Tables


Book Description

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.




Multiway Contingency Tables Analysis for the Social Sciences


Book Description

This book describes the principles and techniques needed to analyze data that form a multiway contingency table. Wickens discusses the description of association in such data using log-linear and log-multiplicative models and defines how the presence of association is tested using hypotheses of independence and quasi-independence. The application of the procedures to real data is then detailed. This volume does not presuppose prior experience or knowledge of statistics beyond basic courses in fundamentals of probability and statistical inference. It serves as an ideal reference for professionals or as a textbook for graduate or advanced undergraduate students involved in statistics in the social sciences.




Introductory Business Statistics 2e


Book Description

Introductory Business Statistics 2e aligns with the topics and objectives of the typical one-semester statistics course for business, economics, and related majors. The text provides detailed and supportive explanations and extensive step-by-step walkthroughs. The author places a significant emphasis on the development and practical application of formulas so that students have a deeper understanding of their interpretation and application of data. Problems and exercises are largely centered on business topics, though other applications are provided in order to increase relevance and showcase the critical role of statistics in a number of fields and real-world contexts. The second edition retains the organization of the original text. Based on extensive feedback from adopters and students, the revision focused on improving currency and relevance, particularly in examples and problems. This is an adaptation of Introductory Business Statistics 2e by OpenStax. You can access the textbook as pdf for free at openstax.org. Minor editorial changes were made to ensure a better ebook reading experience. Textbook content produced by OpenStax is licensed under a Creative Commons Attribution 4.0 International License.




The Analysis of Contingency Tables, Second Edition


Book Description

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.




Statistics for the Social Sciences


Book Description

Do your students lack confidence in handling quantitative work? Do they get confused about how to enter statistical data on SAS and SPSS programs? This Second Edition of Mark Sirkin's popular textbook is the solution for these dilemmas. The book progresses from concepts that require little computational work to the more demanding. It emphasizes utilization so that students appreciate the usefulness of statistics and shows how the interpretation of data is related to the methods by which data was obtained. The author includes coverage of the scientific method, levels of measurement and the interpretation of tables.




Metric Scaling


Book Description

Presents a set of closely related techniques that facilitate the exploration and display of a wide variety of multivariate data, both categorical and continuous. Three methods of metric scaling, correspondence analysis, principal components analysis, and multiple dimensional preference scaling are explored in detail for strengths and weaknesses over a wide range of data types and research situations. "The introduction illustrates the methods with a small dataset. This approach is effective--in a few minutes, with no mathematical requirement, the reader can understand the capabilities, similarities, and differences of the methods. . . . Numerical examples facilitate learning. The authors use several examples with small datasets that illustrate very well the links and the differences between the methods. . . . we find this text very good and recommend it for graduate students and social science researchers, especially those who are interested in applying some of these methods and in knowing the relationship among them." --Journal of Marketing Research "Illustrate[s] the service Sage provides by making high-quality works on research methods available at modest prices. . . . The authors use several interesting examples of practical applications on data sets, ranging from contraception preferences, to pottery shards from archeological digs, to durable consumer goods from market research. These examples indicate the broad range of possible applications of the method to social science data." --Contemporary Sociology "The book is a bargain; it is clearly written." --Journal of Classification