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010 | _z 2012009791 | ||
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020 | _z9781118146408 | ||
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049 | _aMAIN | ||
100 | 1 | _aEye, Alexander von. | |
245 | 1 | 0 |
_aLog-linear modeling : _bconcepts, interpretation, and application / _cAlexander von Eye, Michigan State University, Department of Psychology, East Lansing, MI, Eun-Young Mun, Rutgers, the State University of New Jersey, Center for Alcohol Studies, Piscataway, New Jersey. |
260 |
_aHoboken, New Jersey : _bWiley, _c[2013] |
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300 |
_a1 online resource (xv, 450 pages) : _billustrations |
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336 |
_atext _btxt _2rdacontent |
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337 |
_acomputer _bc _2rdamedia |
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338 |
_aonline resource _bcr _2rdacarrier |
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347 |
_adata file _2rda |
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380 | _aBibliography | ||
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"-- _cProvided by publisher. |
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504 | _aIncludes bibliographical references and indexes. | ||
588 | 0 | _aPrint version record. | |
505 | 0 | _aBasics of Hierarchical Log-Linear Models -- Effects in a Table -- Goodness-of-Fit -- Hierarchical Log-Linear Models and Odds Ratio Analysis -- Computations I: Basic Log-Linear Modeling -- The Design Matrix Approach -- Parameter Interpretation and Significance Tests -- Computations II: Design Matrices and Poisson GLM -- Nonhierarchical and Nonstandard Log-Linear Models -- Computations III: Nonstandard Models -- Sampling Schemes and Chi-Square Decomposition -- Symmetry Models -- Log-Linear Models of Rater Agreement -- Comparing Associations in Subtables: Homogeneity of Associations -- Logistic Regression and Other Logit Models -- Reduced Designs -- Computations IV: Additional Models. | |
650 | 0 | _aLog-linear models. | |
650 | 7 |
_aMATHEMATICS _xProbability & Statistics _xGeneral. _2bisacsh |
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650 | 7 |
_aMATHEMATICS _xProbability & Statistics _xRegression Analysis. _2bisacsh |
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650 | 7 |
_aLog-linear models. _2fast _0(OCoLC)fst01001918 |
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655 | 4 | _aElectronic books. | |
655 | 7 |
_aElectronic books. _2local |
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700 | 1 | _aMun, Eun Young. | |
776 | 0 | 8 |
_iPrint version: _aEye, Alexander von. _tLog-linear modeling. _dHoboken, New Jersey : Wiley, [2013] _z9781118146408 _w(DLC) 2012009791 _w(OCoLC)779259318 |
856 | 4 | 0 |
_uhttp://dx.doi.org/10.1002/9781118391778 _zWiley Online Library |
994 |
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