6. 2 The Two-Sample Capture-Recapture Problem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 231 6. 3 Conditional Maximum Likelihood Estimation of N . . . . . . . . . . . . . . . . . . . . . . 236 6. 4 The Three-Sample Census . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 237 6. 5 The General Multiple Recapture Problem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 246 6. 6 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ....

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.