The Analysis of Cross-Classified Categorical DataSpringer Science & Business Media, 2007. 8. 6. - 198페이지 A variety of biological and social science data come in the form of cross-classified tables of counts, commonly referred to as contingency tables. Until recent years the statistical and computational techniques available for the analysis of cross-classified data were quite limited. This book presents some of the recent work on the statistical analysis of cross-classified data using longlinear models, especially in the multidimensional situation. |
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Amer analysis associated asymptotic asymptotic variances attitude binary Bishop Bradley-Terry model causal chi-square statistic coefficients collapsing column compute contingency tables continuation ratios corresponding cross-classification cross-product ratio data in Table degrees of freedom described discussion estimated expected cell estimated expected values estimated u-terms example expected cell values explanatory variables expression Fienberg fits the data fitted model fixed by design Goodman goodness-of-fit goodness-of-fit statistics Haberman 1974a incomplete independence involving iterative proportional fitting Kullback Larntz level of significance likelihood equations likelihood function likelihood-ratio statistic likelihood-ratio test linear logistic logistic regression logit models loglinear models methods minimal sufficient statistics MLEs model of quasi-independence multidimensional contingency tables n₂ observed counts pair parameters path diagrams perch diameter perch height Poisson probability problems product-multinomial recursive systems response variable sampling model sampling scheme sampling zeros Section standard sufficient statistics systems of logit test statistic three-factor two-factor x² distribution Xijk