UID:
almafu_9959328835802883
Format:
1 online resource (xv, 710 pages) :
,
illustrations
Edition:
2nd ed.
ISBN:
0471458767
,
9780471458760
,
9781280366291
,
9780471360933
,
0471360937
,
0471249688
,
9780471249689
,
128036629X
,
9786610366293
,
6610366292
Series Statement:
Wiley series in probability and statistics
Content:
The use of statistical methods for categorical data has increased dramatically, particularly for applications in the biomedical and social sciences. Responding to new developments in the field as well as to the needs of a new generation of professionals and students, this new edition of the classic Categorical Data Analysis offers a comprehensive introduction to the most important methods for categorical data analysis.
Note:
First edition: ©1990.
,
Introduction : distributions and inference for categorical data -- Describing contingency tables -- Inference for contingency tables -- Introduction to generalized linear models -- Logistic regression -- Building and applying logistic regression models -- Logit models for multinomial responses -- Loglinear models for contingency tables -- Building and extending loglinear/logit models -- Models for matched pairs -- Analyzing repeated categorical response data -- Random effects : generalized linear mixed models for categorical responses -- Other mixture models for categorical data -- Asymptotic theory for parametric models -- Alternative estimation theory for parametric models -- Historical tour of categorical data analysis.
Additional Edition:
Print version: Agresti, Alan. Categorical data analysis. Hoboken, N.J. : Wiley-Interscience, ©2002 ISBN 0471360937
Language:
English
Subjects:
Economics
,
Biology
,
Psychology
,
Mathematics
,
Sociology
Keywords:
Electronic books.
;
Electronic books.
;
Electronic books.
;
Electronic books.
;
Electronic books.
;
Electronic books.
URL:
https://onlinelibrary.wiley.com/doi/book/10.1002/0471249688
URL:
https://onlinelibrary.wiley.com/doi/book/10.1002/0471249688
URL:
https://onlinelibrary.wiley.com/doi/book/10.1002/0471249688
