Abstract

Journal of the Royal Statistical Society: Series B (Methodological)Volume 52, Issue 1 p. 51-72 DiscussionFree Access Discussion of the Papers by Edwards, and Wermuth and Lauritzen First published: 1990 https://doi.org/10.1111/j.2517-6161.1990.tb01772.xCitations: 1AboutPDF ToolsExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat REFERENCES IN THE DISCUSSION Aalen, O. (1987) Dynamic modeling and causality. Scand. Act. J., 177– 190. Amemiya, T. (1985) Advanced Econometrics. Cambridge: Harvard University Press. Arminger, G. and Schoenberg, R. (1989) Pseudo maximum likelihood estimation and a test for misspecification in mean and covariance structure models. Psychometrika, to be published. Barndorff-Nielsen, O. E. and Blæsild, P. (1988) Combination of reproductive models. Ann. Statist., 16, 323– 334. Bártfai, P. and Rudas, T. (1988) Conditionally independent extension of measures. Preprint 57/1988. Mathematical Institute, Hungarian Academy of Sciences. Birch, M. W. (1963) Maximum likelihood in three-way contingency tables. J. R. Statist. Soc. B, 25, 220– 233. Cook, R. D. and Weisberg, S. (1982) Residuals and Influence in Regression. New York: Chapman and Hall. Darroch, J. N., Lauritzen, S. L. and Speed, T. P. (1980) Markov fields and log-linear interaction models for contingency tables. Ann. Statist., 8, 522– 539. Dawid, A. P. (1979a) Conditional independence in statistical theory (with discussion). J. R. Statist. Soc. B, 41, 1– 31. Dawid, A. P. (1979b) Some misleading arguments involving conditional independence. J. R. Statist. Soc. B, 41, 249– 252. Deming, W. E. and Stephan, F. F. (1940) On a least squares adjustment of a sampled frequency table when the expected marginal totals are known. Ann. Math. Statist., 11, 427– 444. Dempster, A., Laird, N. and Rubin, D. (1977) Maximum-likelihood from incomplete data via the EM algorithm. J. R. Statist. Soc. B, 39, 1– 38. Edwards, D. and Havránek, T. (1985) A fast procedure for model search in multidimensional contingency tables. Biometrika, 72, 339– 351. Edwards, D. and Havránek, T. (1987) A fast model selection procedure for large families of models. J. Am. Statist. Ass., 82, 205– 213. Fienberg, S. E. (1970) Quasi-independence and maximum likelihood estimation in incomplete contingency tables. J. Am. Statist. Ass., 65, 1610– 1616. Foutz, R. V. and Srivastava, R. C. (1977) The performance of the likelihood ratio test when the model is incorrect. Ann. Statist., 5, 1183– 1194. Frydenberg, M. (1986) Blandede interaktions modellar, kausale modeller, kollapsibilitet og estimation. Statistike Interna 42. Aarhus University. Frydenberg, M. (1989) The chain graph Markov property. Research Report 186. Department of Theoretical Statistics, Aarhus University. Frydenberg, M. (1990) Marginalization and collapsibility in graphical interaction models. Research Report 166. Department of Theoretical Statistics, Aarhus University. Frydenberg, M. and Lauritzen, S. L. (1989) Decomposition of maximum-likelihood in mixed interaction models. Biometrika, 76, in the press. Glymour, C., Scheines, R., Sprites, P. and Kelly, K. (1987) Discovering Causal Structure: Artificial Intelligence, Philosophy of Science, and Statistical Modelling. New York: Academic Press. Goodman, L. A. (1969) On partitioning χ2 and detecting partial association in three-way contingency tables. J. R. Statist. Soc. B, 31, 486– 498. Goodman, L. A. (1970) The multivariate analysis of qualitative data: interactions among multiple classifications. J. Am. Statist. Ass., 65, 226– 256. Goodman, L. A. (1971a) The analysis of multidimensional contingency tables: stepwise procedures and direct estimation methods for building models for multiple classifications. Technometrics, 18, 33– 61. Goodman, L. A. (1971b) Partitioning of chi-square, analysis of marginal contingency tables, and estimation of expected frequencies in multidimensional contingency tables. J. Am. Statist. Ass., 66, 339– 344. Goodman, L. A. (1972) A general model for the analysis of surveys. Am. J. Sociol., 77, 1035– 1086. Goodman, L. A. (1973a) The analysis of multidimensional contingency tables when some variables are posterior to others: A modified path analysis approach. Biometrika, 60, 179– 192. Goodman, L. A. (1973b) Causal analysis of data from panel studies and other kinds of surveys. Am. J. Sociol., 78, 1135– 1191. Goodman, L. A. (1974a) Exploratory latent structure analysis using both identifiable and unidentifiable models. Biometrika, 61, 215– 231. Goodman, L. A. (1974b) The analysis of systems of qualitative variables when some variables are unobservable: I, A modified latent structure approach. Am. J. Sociol., 79, 1179– 1259. Goodman, L. A. (1979) A brief guide to the causal analysis of data from surveys. Am. J. Sociol., 84, 1078– 1095. Goodman, L. A. (1981) Criteria for determining whether certain categories in a cross-classification table should be combined, with special reference to occupational categories in an occupational mobility table. Am. J. Sociol., 86, 612– 650. Goodman, L. A. (1985a) Discussion of papers by Wermuth and Lauritzen and Wermuth. Bull. Int. Statist. Inst., 51, 183– 184. Goodman, L. A. (1985b) The analysis of cross-classified data having ordered and/or unordered categories: Association models, correlation models, and asymmetry models for contingency tables with or without missing entries. Ann. Statist., 13, 10– 69. Goodman, L. A. (1986) Some useful extensions of the usual correspondence analysis approach and the usual log-linear models approach in the analysis of contingency tables. Int. Statist. Rev., 54, 243– 309. Gourieroux, C., Monfort, A. and Trognon, A. (1984) Pseudo maximum likelihood methods: theory. Econometrica, 52, 681– 700. Haberman, S. J. (1978) Analysis of Qualitative Data, vol. 1. New York: Academic Press. Holland, P. W. (1986) Statistics and causal inference (with discussion). J. Am. Statist. Ass., 81, 945– 970. Holland, P. W. (1988) Causal inference and path analysis. In Sociological Methodology 1988 (ed. C. Clogg). Washington DC: American Sociological Association. Howard, R. A. (1989) From influence to relevance to knowledge. In Influence Diagrams, Belief Nets and Decision Analysis (eds R. O. Oliver and J. Q. Smith). New York: Wiley. to be published. Johnson, N. L. and Kotz, S. (1975) On some generalized Farlie–Gumbel–Morgenstern distributions. Communs Statist., 4, 415– 427. Jöreskog, K. G. and Sörbom, D. (1988) LISREL 7: A Guide to the Program and Applications. Chicago: SPSS Inc. K. G. Jöreskog and H. O. Wold (eds) (1982) Systems under Indirect Observation: Causality, Structure Prediction, parts I and II. Amsterdam: North-Holland. Jupp, P. E. and Mardia, K. V. (1980) A general correlation coefficient for directional data and related regression problems. Biometrika, 67, 163– 173. Kent, J. T. (1982) Robust properties of likelihood ratio tests. Biometrika, 69, 19– 27. Kiiveri, H. T. (1983) A unified theory of causal models. PhD Thesis. University of Western Australia, Perth. Kiiveri, H. T. (1987) An incomplete data approach to the analysis of covariance structures. Psychometrika, 52, 539– 554. Krzanowski, W. J. (1983) Distance between populations using mixed continuous and categorical variables. Biometrika, 70, 235– 243. Lauritzen, S. L. (1979) Lectures on Contingency Tables, 1st edn. Aalborg: Aalborg University Press. Lauritzen, S. L. (1989) Mixed graphical association models. Scand. J. Statist., 16, in the press. Lauritzen, S. L., Dawid, A. P., Larsen, B. N. and Leimer H.-G. (1988) Independence properties of directed Markov fields. Research Report R-88-32. Institute of Electronic Systems, Aalborg University. Lauritzen, S. L. and Wermuth, N. (1989) Graphical models for associations between variables, some of which are qualitative and some quantitative. Ann. Statist., 17, 31– 54. Leimer, H.-G. (1985) Streng zerlegbare Graphen. Doctoral Thesis. Johannes Gutenberg-Universität, Mainz. Leimer, H.-G. (1989) Triangulated graphs with marked vertices. Ann. Discr. Math., 41, 311– 324. Mardia, K. V., Kent, J. T. and Bibby, J. M. (1979) Multivariate Analysis. London: Academic Press. Mykland, P. (1986) Statistical causality. Technical Report. Department of Mathematics, University of Bergen. Olkin, I. and Tate, R. F. (1961) Multivariate correlation models with mixed discrete and continuous variables. Ann. Math. Statist., 32, 448– 465. Pearl, J. (1988) Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference. San Mateo: Morgan Kaufman. Picci, G. and Pinzoni, S. (1986) A new class of dynamic models for stationary time series. Lecture Notes Contr. Inform. Sci., 86. Smith, J. Q. (1989) Influence diagrams for statistical modelling. Ann. Statist., 17, in the press. Street, A. P. and Wallis, W. D. (1982) Combinatorics: A First Course, ch. XII, theorem 3. st Pierre: Charles Babbage Research Centre. Victor, N. (1983) A note on contingency tables with one structural zero. Biometrics J., 25, 283– 289. Wermuth, N. (1976) Analogies between multiplicative models in contingency tables and covariance selection. Biometrics, 32, 95– 108. Wermuth, N. (1988) Block-recursive linear regression equations. Berichte zur Stochastik und Verwandten Gebieten, 88-4. Mainz: Johannes Gutenberg-Universität. Whittaker, J. (1990) Graphical Models in Applied Multivariate Statistics. Chichester: Wiley. Citing Literature Volume52, Issue11990Pages 51-72 This article also appears in:Discussion Papers ReferencesRelatedInformation

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call