4 edition of The analysis of categorical data using GLIM found in the catalog.
Includes bibliographical references (p. -168).
|Statement||James K. Lindsey.|
|Series||Lecture notes in statistics ;, 56, Lecture notes in statistics (Springer-Verlag) ;, v. 56.|
|LC Classifications||QA279 .L58 1989|
|The Physical Object|
|Pagination||v, 168 p. ;|
|Number of Pages||168|
|LC Control Number||90103866|
Using Computer Software to Analyze Categorical Data In this appendix we discuss statistical software for categorical data analysis, with emphasis on SAS. We begin by mentioning major software that can perform the analyses discussed in this book. Then we illustrate, by chapter, SAS code for the analyses. Information about other packages such as. The term “categorical data” is just another name for “nominal scale data”. It’s nothing that we haven’t already discussed, it’s just that in the context of data analysis people tend to use the term “categorical data” rather than “nominal scale data”. I don’t know why. In any case, categorical data.
Categorical Data Analysis by Example Book Description: Introduces the key concepts in the analysis of categorical data with illustrative examples and accompanying R code.. This book is aimed at all those who wish to discover how to analyze categorical data without getting immersed in complicated mathematics and without needing to wade through a large amount of prose. Categorical data, as the name implies, is grouped into some sort of category or multiple categories. For example, if I were to collect information about a person's pet preferences, I would have to.
To make a graphical display of categorical data, it is a necessary condition. Analysis of categorical data very often includes data tables. The values are represented as a two-way table or contingency table by counting the number of items that are into each category. Here is an example of a categorical data two-way table for a group of 50 people. Book Description. Learn How to Properly Analyze Categorical Data Analysis of Categorical Data with R presents a modern account of categorical data analysis using the popular R software. It covers recent techniques of model building and assessment for binary, multicategory, and count response variables and discusses fundamentals, such as odds ratio and probability estimation.
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Given the importance of the analysis of categorical data using log linear models within the overall body of models known as general linear models (GLMs) treated by GLIM, this book should be of interest to anyone, in any field, concerned with such applications.
It should be suitable as a manual for applied statistics courses covering this subject. The analysis of categorical data using GLIM. [James K Lindsey] Home. WorldCat Home About WorldCat Help. Search. Search for Library Items Search for Lists Search for Contacts Search for a Library.
Create Book\/a>, schema:CreativeWork\/a> ; \u00A0\u00A0\u00A0 library. Get this from a library. The Analysis of Categorical Data Using GLIM. [James K Lindsey] -- This book shows how to apply log linear and logistic models to categorical data using GLIM.
Each model is illustrated by a numerical example. All of the necessary programs in the GLIM macro language. Statistical Methods for Categorical Data Analysis. 2 nd Edition.
Daniel A. Powers and Yu Xie. Statistical Methods for Categorical Data Analysis by Daniel A. Powers and Yu Xie provides a comprehensive introduction to methods and models for categorical data analysis and their applications in social science research.
An explicit aim of the book is to integrate the transformational and the latent. Analysis of Ordinal Categorical Data (Wiley Series in Probability and Statistics Book ) - Kindle edition by Agresti, Alan.
Download it once and read it on your Kindle device, PC, phones or tablets. Use features like bookmarks, note taking and highlighting while reading Analysis of Ordinal Categorical Data (Wiley Series in Probability and Statistics Book )/5(4).
Website for CATEGORICAL DATA ANALYSIS, 3rd edition For the third edition of Categorical Data Analysis by Alan Agresti (Wiley, ), this site contains (1) information on the use of other software (SAS, R and S-plus, Stata, SPSS, and others), (2) data sets for examples and many exercises (for many of which, only excerpts were shown in the text itself), (3) short answers for some of the.
Statistical science’s first coordinated manual of methods for analyzing ordered categorical data, now fully revised and updated, continues to present applications and case studies in fields as diverse as sociology, public health, ecology, marketing, and pharmacy.
Analysis of Ordinal Categorical Data, Second Edition provides an introduction to basic descriptive and inferential methods for. Learn How to Properly Analyze Categorical Data Analysis of Categorical Data with R presents a modern account of categorical data analysis using the popular R software.
It covers recent techniques of model building and assessment for binary, multicategory, and count response variables and discusses fundamentals, such as odds ratio and probability by: GLIM See first edition of "Categorical Data Analysis" () for several GLIM examples, as well as the text by Aitkin, Francis, and Hinde on "Statistical Modeling in GLIM4" (Oxford) and Jim Lindsey's text on "The Analysis of Categorical Data Using GLIM" (Springer-Verlag).
See Statlib for an archive of GLIM macros. 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. Book Review; Published: December Lindsey, J.: The analysis of categorical data using GLIM. Lecture Notes in Statistics, Vol. Springer Verlag, Berlin Author: G. Arminger. Analysis of Qualitative Data Using GLIM: Two Examples Based on Shopping Survey Data Article in The Professional Geographer 34(1) - 90 February with 14 Reads How we measure 'reads'.
Categorical Data Analysis Using the SAS System, 2nd edn. Cary, NC: SAS Institute Inc. Zelterman, D. Models for Discrete Data. Oxford: Oxford University Press. Course Description: This course surveys theory and methods for the analysis of categorical response and count data.
List of analyses of categorical data. Jump to navigation Jump to search. This a list of statistical procedures which can be used for the analysis of categorical data, also known as data on the nominal scale and as categorical variables General tests.
Bowker's test of symmetry; Categorical distribution, general model; Chi-squared test. existing data set, such as one derived from maps, for GLIMS. A GLIMS Analysis Session is defined as the activity of producing a set of glacier outlines, together with GLIMS attribute data, usually from a single image.
A GLIMS Analysis (without the “Session”) is one snapshot of one Size: KB. The Analysis of Categorical Data Using GLIM (Lecture Notes in Statistics) The Analysis of Categorical Data Using GLIM.
James K. Lindsey. Published by Springer. ISBN ISBN 13 Poor. This is an ex-library book and may have the usual library/used-book markings book has hardback covers. In poor condition, suitable. “ftoc” — /1/31 — pagev—#1 Contents Preface to the Second Edition xv 1.
Introduction 1 Categorical Response Data, 1 Response/ExplanatoryVariable Distinction, 2 Nominal/Ordinal Scale Distinction, 2 Organization of this Book, 3. Offers data sets, R programs, and videos on the book’s website; Solutions manual available upon qualifying course adoption.
Summary. Learn How to Properly Analyze Categorical Data Analysis of Categorical Data with R presents a modern account of categorical data analysis using the popular R software.
It covers recent techniques of model. The aim of this book is to present a survey of the many ways in which the statistical package GLIM may be used to model and analyze stochastic processes. Its emphasis is on using GLIM Author: Murray Aitkin.
Categorical Data Analysis by Example is a reference for students in statistics and researchers in other disciplines, especially the social sciences, who use categorical data. This book is also a reference for practitioners in market research, medicine, and other :.
GLIM files used in Xie ASR paper. GLIM files used in Xie and Efron JASA paper. GLIM files for some examples in Powers and Xie book on statistical methods for categorical data analysis. STATA Programs. Type "ssc install rc2 " in STATA.
This is a STATA program written by John Hendrickx for estimating Goodman's RC model from cross.Appendix A discusses the use of computer software to analyze categorical data, with special emphasis on SAS. After surveying the major software packages for categorical data analysis, it gives examples of SAS Code for methods in each chapter in the text, illustrating with many of the text examples.Analysis of Categorical Data with R presents a modern account of categorical data analysis using the popular R software.
It covers recent techniques of model building and assessment for binary, multicategory, and count response variables and discusses fundamentals, such as odds ratio and probability estimation/5(6).