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Author: Brian S. Everitt
Publisher: CRC Press
ISBN: 9780412398506
Category : Mathematics
Languages : en
Pages : 178
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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.
Author: Brian S. Everitt
Publisher: CRC Press
ISBN: 9780412398506
Category : Mathematics
Languages : en
Pages : 178
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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.
Author: Brian S. Everitt
Publisher: Chapman and Hall/CRC
ISBN: 9780412296802
Category : Mathematics
Languages : en
Pages : 168
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Book Description
Author: Brian Everitt
Publisher: Chapman and Hall/CRC
ISBN:
Category : Computers
Languages : en
Pages : 148
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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.
Author: Brian Everitt
Publisher: Chapman & Hall
ISBN:
Category : Mathematics
Languages : en
Pages : 148
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Book Description
Contingency tables and the chi-square test; Multidimensional tables; Log-linear models for contigency tables; Some special types of contigency tables.
Author: Alan Agresti
Publisher: John Wiley & Sons
ISBN: 1119405270
Category : Mathematics
Languages : en
Pages : 400
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Book Description
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.
Author: Tamás Rudas
Publisher: SAGE
ISBN: 9780761903628
Category : Mathematics
Languages : en
Pages : 92
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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.
Author: Stephen E. Fienberg
Publisher: Springer Science & Business Media
ISBN: 0387728252
Category : Mathematics
Languages : en
Pages : 208
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Book Description
A variety of biological and social science data come in the form of cross-classified tables of counts, commonly referred to as contingency tables. Until recent years the statistical and computational techniques available for the analysis of cross-classified data were quite limited. This book presents some of the recent work on the statistical analysis of cross-classified data using longlinear models, especially in the multidimensional situation.
Author: Morten Fagerland
Publisher: CRC Press
ISBN: 1466588187
Category : Mathematics
Languages : en
Pages : 657
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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.
Author: Jacob Cohen
Publisher: Routledge
ISBN: 1134742770
Category : Psychology
Languages : en
Pages : 625
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Book Description
Statistical Power Analysis is a nontechnical guide to power analysis in research planning that provides users of applied statistics with the tools they need for more effective analysis. The Second Edition includes: * a chapter covering power analysis in set correlation and multivariate methods; * a chapter considering effect size, psychometric reliability, and the efficacy of "qualifying" dependent variables and; * expanded power and sample size tables for multiple regression/correlation.
Author: Roderick J. A. Little
Publisher: John Wiley & Sons
ISBN: 1118595696
Category : Mathematics
Languages : en
Pages : 463
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Book Description
An up-to-date, comprehensive treatment of a classic text on missing data in statistics The topic of missing data has gained considerable attention in recent decades. This new edition by two acknowledged experts on the subject offers an up-to-date account of practical methodology for handling missing data problems. Blending theory and application, authors Roderick Little and Donald Rubin review historical approaches to the subject and describe simple methods for multivariate analysis with missing values. They then provide a coherent theory for analysis of problems based on likelihoods derived from statistical models for the data and the missing data mechanism, and then they apply the theory to a wide range of important missing data problems. Statistical Analysis with Missing Data, Third Edition starts by introducing readers to the subject and approaches toward solving it. It looks at the patterns and mechanisms that create the missing data, as well as a taxonomy of missing data. It then goes on to examine missing data in experiments, before discussing complete-case and available-case analysis, including weighting methods. The new edition expands its coverage to include recent work on topics such as nonresponse in sample surveys, causal inference, diagnostic methods, and sensitivity analysis, among a host of other topics. An updated “classic” written by renowned authorities on the subject Features over 150 exercises (including many new ones) Covers recent work on important methods like multiple imputation, robust alternatives to weighting, and Bayesian methods Revises previous topics based on past student feedback and class experience Contains an updated and expanded bibliography The authors were awarded The Karl Pearson Prize in 2017 by the International Statistical Institute, for a research contribution that has had profound influence on statistical theory, methodology or applications. Their work "has been no less than defining and transforming." (ISI) Statistical Analysis with Missing Data, Third Edition is an ideal textbook for upper undergraduate and/or beginning graduate level students of the subject. It is also an excellent source of information for applied statisticians and practitioners in government and industry.
