LEADER 02361nas 2200457 n 450 001 990008993710403321 005 20240229084438.0 011 $a0002-8223 035 $a000899371 035 $aFED01000899371 035 $a(Aleph)000899371FED01 035 $a000899371 091 $2CNR$aP 00000656 100 $a20161109a19259999km-y0itaa50------ba 101 0 $aeng 102 $aUS 110 $aauu-------- 200 1 $aJournal of the American Dietetic Association 207 1$a1925- 210 $aChicago$cAmerican dietetic association 452 0$12001$aJournal of the American Dietetic Association 530 0 $aJournal of the American Dietetic Association 675 $a613.2 676 $a613 712 02$aAmerican Dietetic Association 801 0$aIT$bACNP$c20090723 859 4 $uhttp://acnp.cib.unibo.it/cgi-ser/start/it/cnr/dc-p1.tcl?catno=297&person=false&language=ITALIANO&libr=&libr_th=unina1$zBiblioteche che possiedono il periodico 901 $aSE 912 $a990008993710403321 958 $aBiblioteca. Dipartimento delle Scienze Biologiche Sezione di Fisiologia$b1944-1948;$c1947;$fDFGA 958 $aBiblioteca Centrale. Facoltà di Farmacia. Polo delle Scienze e delle Tecnologie per la Vita. Università "Federico II" Napoli$b1976-1987;$c1982;1984-1985;1987;$d68(1976)-87(1987);$fFFABC 958 $aBiblioteca del Dipartimento di Medicina Clinica e Sperimentale$b1981-2004;$c1983;1984;$fDMECM 959 $aDFGA 959 $aFFABC 959 $aDMECM 996 $aJournal of the American Dietetic Association$9794252 997 $aUNINA AP1 8 $6866-01$aNA009 Biblioteca. Dipartimento delle Scienze Biologiche Sezione di Fisiologia$ev. Mezzocannone,8, 80134 Napoli (NA)$m0812535084$m0812535032$nit AP1 8 $6866-02$aNA074 Biblioteca Centrale. Facoltà di Farmacia. Polo delle Scienze e delle Tecnologie per la Vita. Università "Federico II" Napoli$evia D. Montesano, 49, 80131 Napoli (NA)$m(081)678201/202/204$m(081) 678139$nit AP1 8 $6866-03$aNA172 Biblioteca del Dipartimento di Medicina Clinica e Sperimentale$eVia Sergio Pansini, 5, 80131 Napoli (NA)$m(081) 7462015$m081 7462015$nit AP2 40$aacnp.cib.unibo.it$nACNP Italian Union Catalogue of Serials$uhttp://acnp.cib.unibo.it/cgi-ser/start/it/cnr/df-p.tcl?catno=297&language=ITALIANO&libr=&person=&B=1&libr_th=unina&proposto=NO LEADER 06087nam 2200649 a 450 001 9910141472403321 005 20240516163531.0 010 $a1-118-39176-4 010 $a1-118-39177-2 010 $a1-283-97796-6 010 $a1-118-39174-8 035 $a(CKB)2670000000327898 035 $a(EBL)918213 035 $a(OCoLC)826853571 035 $a(SSID)ssj0000820045 035 $a(PQKBManifestationID)11459498 035 $a(PQKBTitleCode)TC0000820045 035 $a(PQKBWorkID)10856266 035 $a(PQKB)10066404 035 $a(OCoLC)825767800 035 $a(MiAaPQ)EBC918213 035 $a(Au-PeEL)EBL918213 035 $a(CaPaEBR)ebr10648815 035 $a(CaONFJC)MIL429046 035 $a(EXLCZ)992670000000327898 100 $a20120306d2013 ub 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aLog-linear modeling $econcepts, interpretation, and application /$fAlexander von Eye, Eun-Young Mun 205 $a1st ed. 210 $aHoboken, N.J. $cWiley$d2013 215 $a1 online resource (468 p.) 300 $aDescription based upon print version of record. 311 $a1-118-14640-9 320 $aIncludes bibliographical references and indexes. 327 $aCover; Title Page; Copyright Page; CONTENTS; Preface; Acknowledgments; 1 Basics of Hierarchical Log-linear Models; 1.1 Scaling: Which Variables Are Considered Categorical?; 1.2 Crossing Two or More Variables; 1.3 Goodman's Three Elementary Views of Log-linear Modeling; 1.4 Assumptions Made for Log-linear Modeling; 2 Effects in a Table; 2.1 The Null Model; 2.2 The Row Effects-Only Model; 2.3 The Column Effects-Only Model; 2.4 The Row- and Column-Effects Model; 2.5 Log-Linear Models; 3 Goodness-of-Fit; 3.1 Goodness-of-Fit I: Overall Fit Statistics; 3.1.1 Selecting between X2 and G2 327 $a3.1.2 Degrees of Freedom3.2 Goodness-of-Fit II: R2 Equivalents and Information Criteria; 3.2.1 R2 Equivalents; 3.2.2 Information Criteria; 3.3 Goodness-of-Fit III: Null Hypotheses Concerning Parameters; 3.4 Goodness-of-fit IV: Residual Analysis; 3.4.1 Overall Goodness-of-Fit Measures and Residuals; 3.4.2 Other Residual Measures; 3.4.3 Comparing Residual Measures; 3.4.4 A Procedure to Identify Extreme Cells; 3.4.5 Distributions of Residuals; 3.5 The Relationship between Pearson's X2 and Log-linear Modeling; 4 Hierarchical Log-linear Models and Odds Ratio Analysis 327 $a6.1.2 Poisson Models6.1.3 GLM for Continuous Outcome Variables; 6.2 Design Matrices: Coding; 6.2.1 Dummy Coding; 6.2.2 Effect Coding; 6.2.3 Orthogonality of Vectors in Log-linear Design Matrices; 6.2.4 Design Matrices and Degrees of Freedom; 7 Parameter Interpretation and Significance Tests; 7.1 Parameter Interpretation Based on Design Matrices; 7.2 The Two Sources of Parameter Correlation: Dependency of Vectors and Data Characteristics; 7.3 Can Main Effects Be Interpreted?; 7.3.1 Parameter Interpretation in Main Effect Models; 7.3.2 Parameter Interpretation in Models with Interactions 327 $a7.4 Interpretation of Higher Order Interactions8 Computations II: Design Matrices and Poisson GLM; 8.1 GLM-Based Log-linear Modeling in R; 8.2 Design Matrices in SYSTAT; 8.3 Log-linear Modeling with Design Matrices in lEM; 8.3.1 The Hierarchical Log-linear Modeling Option in lEM; 8.3.2 Using lEM'S Command cov to Specify Hierarchical Log-linear Models; 8.3.3 Using lEM'S Command fac to Specify Hierarchical Log-linear Models; 9 Nonhierarchical and Nonstandard Log-linear Models; 9.1 Defining Nonhierarchical and Nonstandard Log-linear Models 327 $a9.2 Virtues of Nonhierarchical and Nonstandard Log-linear Models 330 $a"Over the past ten years, there have been many important advances in log-linear modeling, including the specification of new models, in particular non-standard models, and their relationships to methods such as Rasch modeling. While most literature on the topic is contained in volumes aimed at advanced statisticians, Applied Log-Linear Modeling presents the topic in an accessible style that is customized for applied researchers who utilize log-linear modeling in the social sciences. The book begins by providing readers with a foundation on the basics of log-linear modeling, introducing decomposing effects in cross-tabulations and goodness-of-fit tests. Popular hierarchical log-linear models are illustrated using empirical data examples, and odds ratio analysis is discussed as an interesting method of analysis of cross-tabulations. Next, readers are introduced to the design matrix approach to log-linear modeling, presenting various forms of coding (effects coding, dummy coding, Helmert contrasts etc.) and the characteristics of design matrices. The book goes on to explore non-hierarchical and nonstandard log-linear models, outlining ten nonstandard log-linear models (including nonstandard nested models, models with quantitative factors, logit models, and log-linear Rasch models) as well as special topics and applications. A brief discussion of sampling schemes is also provided along with a selection of useful methods of chi-square decomposition. Additional topics of coverage include models of marginal homogeneity, rater agreement, methods to test hypotheses about differences in associations across subgroup, the relationship between log-linear modeling to logistic regression, and reduced designs. Throughout the book, Computer Applications chapters feature SYSTAT, Lem, and R illustrations of the previous chapter's material, utilizing empirical data examples to demonstrate the relevance of the topics in modern research"--$cProvided by publisher. 606 $aLog-linear models 615 0$aLog-linear models. 676 $a519.5/36 686 $aMAT029000$2bisacsh 700 $aEye$b Alexander von$0148929 701 $aMun$b Eun Young$0920605 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910141472403321 996 $aLog-linear modeling$92064791 997 $aUNINA