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Log-linear modeling :concepts, inter...

Eye, Alexander von.

Log-linear modeling :concepts, interpretation, and application /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Log-linear modeling :Alexander von Eye, Eun-Young Mun.
其他題名:	concepts, interpretation, and application /
其他題名:	Log linear modeling
作者:	Eye, Alexander von.
其他作者:	Mun, Eun Young.
出版者:	Hoboken, New Jersey :Wiley,c2013.
面頁冊數:	xv, 450 p. :ill. ;25 cm.
標題:	Log-linear models.
ISBN:	9781118146408 (hbk.) :

Log-linear modeling :concepts, interpretation, and application /
Eye, Alexander von.

Log-linear modeling :concepts, interpretation, and application /Log linear modelingAlexander von Eye, Eun-Young Mun. - Hoboken, New Jersey :Wiley,c2013. - xv, 450 p. :ill. ;25 cm.

Includes bibliographical references (p. 425-440) and indexes.

"Over the past ten years, there have been many important advances in log-linear modeling, including the specification of new models, in particular non-standard models, and their relationships to methods such as Rasch modeling. While most literature on the topic is contained in volumes aimed at advanced statisticians, Applied Log-Linear Modeling presents the topic in an accessible style that is customized for applied researchers who utilize log-linear modeling in the social sciences. The book begins by providing readers with a foundation on the basics of log-linear modeling, introducing decomposing effects in cross-tabulations and goodness-of-fit tests. Popular hierarchical log-linear models are illustrated using empirical data examples, and odds ratio analysis is discussed as an interesting method of analysis of cross-tabulations. Next, readers are introduced to the design matrix approach to log-linear modeling, presenting various forms of coding (effects coding, dummy coding, Helmert contrasts etc.) and the characteristics of design matrices. The book goes on to explore non-hierarchical and nonstandard log-linear models, outlining ten nonstandard log-linear models (including nonstandard nested models, models with quantitative factors, logit models, and log-linear Rasch models) as well as special topics and applications. A brief discussion of sampling schemes is also provided along with a selection of useful methods of chi-square decomposition. Additional topics of coverage include models of marginal homogeneity, rater agreement, methods to test hypotheses about differences in associations across subgroup, the relationship between log-linear modeling to logistic regression, and reduced designs. Throughout the book, Computer Applications chapters feature SYSTAT, Lem, and R illustrations of the previous chapter's material, utilizing empirical data examples to demonstrate the relevance of the topics in modern research"--

ISBN: 9781118146408 (hbk.) :NT$3121

LCCN: 2012009791Subjects--Topical Terms:

186243
Log-linear models.

LC Class. No.: QA278 / .E95 2013

Dewey Class. No.: 519.5/36

Log-linear modeling :concepts, interpretation, and application /
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100 1 $a Eye, Alexander von. $3 536410
245 1 0 $a Log-linear modeling : $b concepts, interpretation, and application / $c Alexander von Eye, Eun-Young Mun.
246 3 $a Log linear modeling
260 $a Hoboken, New Jersey : $b Wiley, $c c2013.
300 $a xv, 450 p. : $b ill. ; $c 25 cm.
504 $a Includes bibliographical references (p. 425-440) and indexes.
520 $a "Over the past ten years, there have been many important advances in log-linear modeling, including the specification of new models, in particular non-standard models, and their relationships to methods such as Rasch modeling. While most literature on the topic is contained in volumes aimed at advanced statisticians, Applied Log-Linear Modeling presents the topic in an accessible style that is customized for applied researchers who utilize log-linear modeling in the social sciences. The book begins by providing readers with a foundation on the basics of log-linear modeling, introducing decomposing effects in cross-tabulations and goodness-of-fit tests. Popular hierarchical log-linear models are illustrated using empirical data examples, and odds ratio analysis is discussed as an interesting method of analysis of cross-tabulations. Next, readers are introduced to the design matrix approach to log-linear modeling, presenting various forms of coding (effects coding, dummy coding, Helmert contrasts etc.) and the characteristics of design matrices. The book goes on to explore non-hierarchical and nonstandard log-linear models, outlining ten nonstandard log-linear models (including nonstandard nested models, models with quantitative factors, logit models, and log-linear Rasch models) as well as special topics and applications. A brief discussion of sampling schemes is also provided along with a selection of useful methods of chi-square decomposition. Additional topics of coverage include models of marginal homogeneity, rater agreement, methods to test hypotheses about differences in associations across subgroup, the relationship between log-linear modeling to logistic regression, and reduced designs. Throughout the book, Computer Applications chapters feature SYSTAT, Lem, and R illustrations of the previous chapter's material, utilizing empirical data examples to demonstrate the relevance of the topics in modern research"-- $c Provided by publisher.
650 0 $a Log-linear models. $3 186243
650 7 $a MATHEMATICS / Probability & Statistics / General. $2 bisacsh $3 603543
700 1 $a Mun, Eun Young. $3 603542