The Analysis of Cross-Classified Categorical DataSpringer Science & Business Media, 2007. 7. 30. - 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. |
목차
Problems | 23 |
Problems | 51 |
Problems | 68 |
Four and HigherDimensional Contingency Tables | 71 |
Problems | 88 |
Problems | 116 |
Problems | 138 |
Problems | 159 |
References | 177 |
| 191 | |
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자주 나오는 단어 및 구문
approach aptitude associated asymptotic Bishop categorical data causal Chapter chi-square statistic closed-form expressions collapsing column compute conditional independence contingency tables cross-classification cross-product ratio data in Table degrees of freedom described discussion effects entries estimated expected cell estimated expected values estimated u-terms example expected cell values explanatory variables expression Fienberg fit fits the data fixed Goodman goodness-of-fit goodness-of-fit statistics Haberman 1974a height and perch hierarchical loglinear models interaction terms involving iterative proportional fitting Kullback large-sample Larntz level of significance likelihood equations likelihood function likelihood-ratio test linear logistic logistic regression logit models loglinear models marginal table methods mijk MLEs model fits multidimensional contingency tables multidimensional tables multinomial sampling pair parameters partitioning perch diameter perch height Poisson problem product-multinomial recursive systems response variable sampling model sampling scheme sampling zeros saturated model Section standard sufficient statistics systems of logit three-dimensional table three-factor two-factor terms X2 distribution