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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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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analysis application approach appropriate aptitude associated asymptotic Bishop causal cell Chapter chi-square collapsing column comparing complete compute conditional consider contains contingency tables corresponding counts cross-classification data in Table degrees of freedom described discussion distribution effects entries equal equations estimated expected values examined example expected cell explanatory variables expression Fienberg fixed four function give given Goodman goodness-of-fit Haberman illustrate independence individuals interaction interest interpretation involving iterative likelihood linear logit models loglinear models look marginal totals means measure methods MLEs multinomial Note observed pair parameters partitioning perch possible present probability problem procedure proportional provides ratio referred regression relationship response variable sampling sampling model second-order selection significance situations standard statistics structure suggests Suppose test statistic two-dimensional two-factor u-terms usual various zero