|Item type||Location||Collection||Call number||Copy number||Status||Date due|
|E-Book||E-book||Non Fiction||519.536 LIM 1995 (Browse shelf)||Not For Loan|
|Text||Reserve Section||Non Fiction||519.536 LIM 1995 (Browse shelf)||C-1||Not For Loan|
|Text||Circulation Section||Non Fiction||519.536 LIM 1995 (Browse shelf)||C-2||Available|
Includes bibliographical references (p. 275-282) and index.
Categorical data analysis is a special area of generalized linear models which has become the most important area of statistical applications in many disciplines, from medicine to social science. Written for advanced undergraduates, but also useful for statisticians and research workers, this text presents the standard models as well as many newly developed ones in a language which can be applied in many modern statistical packages such as GLIM, GENMSTAT, S-Plus, and SAS and LISP-STAT. Structured around the distinction between independent events occurring to different individuals and repeated events occurring to the same individuals, the book demonstrates that much of modern statistics can be seen as special cases of categorical data models. Other topics covered include Markov chains, overdispersion, and random effects.