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= C.N.R. - I.A.M.I. =
= Istituto per le Applicazioni della Matematica e dell'Informatica =
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AVVISO DI SEMINARI
Da lunedi` 14 a venerdi` 18 Ottobre 1996, dalle ore 14 alle or 16, il
Professor
James H. Albert
Department of Mathematics and Statistics
Bowling Green State University
terra` presso la sede del CNR (via Ampere 56, Milano), un ciclo di
lezioni su
Bayesian Approaches to the Analysis of Cross-Classified Data
Con l'invito ad intervenire, La prego di dare la piu` ampia diffusione
al presente annuncio.
Il Direttore dello IAMI
Eugenio Regazzini
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\begin{document}
\begin{center} {\bf
OUTLINE \\
Bayesian Approaches to the Analysis of Cross-Classified Data \\
14 - 18 October 1996 \\
James Albert, Bowling Green State University}
\end{center}
\begin{enumerate}
\item
Introduction. Classical approaches to the analysis of categorical data
(Bishop, Fienberg and Holland, Agresti). Selecting a log-linear model
and basing inference on the selected model. Difficulties with the use of
these methods.
\item
Early Bayesian analyses of categorical data. Lindley, Good and Jeffreys.
\item
Smoothing tables using Dirichlet distributions (Fienberg, Holland),
mixtures of Dirichlet distributions (Albert and Gupta, Epstein), and
Normal distributions (Leonard, Nazaret, Laird).
\item
Good's tests of equiprobability and independence using Bayes' factors.
\item
Alternative Bayesian tests using Dirichlet priors (Dickey and Gunel, Albert)
and the device of imaginary observations (Smith and Spiegelhalter).
\item
General approach to testing in generalized linear models, (Raftery),
testing using normal priors on interaction terms of the log-linear model
(Albert).
\item
The use of BIC in sociological applications (Raftery).
\item
Interaction analysis of contingency tables (Leonard, Evans, Knuiman and
Speed).
\item
Bayesian model search of log-linear models (Raftery, Magidan, Dellaportas
and Forster, Albert).
\item
Probit model fitting by use of data augmentation and Gibbs sampling.
(Albert and Chib) Extensions to random effects models. Generalizations to
an ordered or unordered multinomial response. Bayesian residuals.
\end{enumerate}
\newpage
\section*{References}
\def\reff#1{\par\hang\hskip-\parindent {#1\/}.} \reff{}
\baselineskip=18pt
\reff{Agresti, A. (1990)} {\it Categorical Data Analysis.} New York: Wiley.
\reff{Albert, J. H. (1987)} Empirical Bayes estimation in contingency tables. {\it Communications in Statistics --- Theory and Methods}, {\bf 16}, 2459-2485.
\reff{Albert, J. H (1989)} A Bayesian Test for a Two-Way Contingency Table
Using Independence Priors, {\it Canadian Journal of Statistics}, {\bf 18},
347-363.
\reff{Albert, J. H. (1996)} Bayesian Selection of Log-Linear Models. {\it
Canadian Journal of Statistics}, to appear.
\reff{Albert, J. H. (1997)} Bayesian Testing and Estimation of Association
in a Two-Way Contingency Table. {\it Journal of the American Statistical
Association}, to appear.
\reff{Albert, J. H. and Chib, S. (1993)} Bayesian analysis of
binary and polychotomous response data, {\it Journal of the American
Statistical Association}, {\bf 88}, 669-679.
\reff{Albert, J. H. and Chib, S. (1995)} Bayesian residual analysis
for binary response regression models. {\it Biometrika}, {\bf 82}, 747-759.
\reff{Albert , J. H. and Chib, S. (1996)} Bayesian probit
modeling of binary repeated measures data with an application to a
cross-over trial. In {\it Bayesian Biostatistics}, (eds. D.
A. Berry and D. K. Stangl), Marcel Dekker, New York, 577-599.
\reff{Albert, J. H. and Gupta, A. K. (1982)} Mixtures of Dirichlet
distributions and estimation in contingency tables.
{\it Annals of Statistics} {\bf 10}, 1261-1268.
\reff{Bishop, Y.M.M., Fienberg, S.E. and Holland, P.W. (1975)}
{\it Discrete Multivariate Analysis.} Cambridge, Mass.: MIT Press.
\reff{Crook, J.F. and Good, I.J. (1980)} On the application of symmetric
Dirichlet distributions and their mixtures to contingency tables: Part II.
{\it Annals of Statistics} {\bf 8}, 1198-1218.
\reff{Dellaportas, P. and Forster, J. J. (1995)} Markov chain Monte Carlo
model determination for hierarchical and graphical log-linear models.
Technical report, Department of Mathematics, University of Southampton.
\reff{Diaconis, P. and Efron, B. (1985)} Testing for Independence in a
Two-Way Table: New Interpretations of the Chi-Square Statistic
{\it Annals of Statistics}, {\bf 13}, 845-874.
\reff{Epstein, L. D. and Fienberg, S. E. (1992)} Bayesian estimation
in multidimensional contingency tables. In {\it
Bayesian Analysis in Statistics and Economics}, P. K. Goel and N. Sreenivas
Iyengar, eds, Springer-Verlag: New York.
\reff{Evans, M., Gilula, Z. and Guttman, I. (1993)} Computational issues
in the Bayesian analysis of categorical data: Log-linear and Goodman's
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\reff{Fienberg, S. E. and Holland, P. W. (1973)} Simultaneous estimation
of multinomial cell probabilities. {\it Journal of the American Statistical
Association} {\bf 68}, 683-689.
\reff{Gelman, A. and Rubin, D. B. (1991)} Simulating the posterior
distribution of loglinear contingency table models. Technical report.
\reff{George, E.I. and McCulloch, R. E. (1993)} Variable selection via
Gibbs sampling. {\it Journal of the American Statistical Association}
{\bf 88}, 881-889.
\reff{Good, I. J. (1965)} {\it The Estimation of Probabilities}, M.I.T. Press.
\reff{Good, I. J. (1967)} A Bayesian significance test for multinomial
distributions. {\it Journal of the Royal Statistical Society, B}, {\bf
29}, 399-431.
\reff{Good, I. J. (1976)} On the application of symmetric Dirichlet
distributions and their mixtures to contingency tables. {\it Annals of
Statistics} {\bf 4}, 1159-1189.
\reff{Good, I. J. and Crook, J. F. (1987)} The robustness and sensitivity
of the mixed-Dirichlet Bayesian test for ``independence'' in contingency
tables. {\it Annals of Statistics} {\bf 15}, 670-693.
\reff{Gunel, E. and Dickey, J. M. (1974)} Bayes factors for independence
in contingency tables. {\it Biometrika} {\bf 61}, 545-557.
\reff{Jeffreys, H. (1961)} {\it Theory of Probability} \rm (3rd ed.),
Oxford: University Press.
\reff{Knuiman and Speed (1988)} Incorporating prior information into
the analysis of contingency tables. {\it Biometrics}, {\bf 44}, 1061-1071.
\reff{Leonard, T. (1975)} Bayesian estimation methods for two-way
contingency tables. {\it Journal of the Royal Statistical Society B},
{\bf 37}, 23-37.
\reff{Leonard, T. (1993)} The Bayesian analysis of categorical data --- a
selective review. In {\it Aspects of Uncertainty (A Tribute to D. V.
Lindley)}, Wiley, NY, 283-310.
\reff{Leonard, T., Hsu, J.S.J. and Tsui, K.W. (1989)} Bayesian marginal
inference. {\it Journal of the American Statistical Association}
{\bf 84}, 1051-1058.
\reff{Leonard, T. and Novick, M. R. (1986)} Bayesian full rank
marginalization for two-way contingency tables. {\it Journal of Educational
Statistics}, {\bf 11}, 33-56.
\reff{Laird, N. M. (1978)} Empirical Bayes methods for two-way
contingency tables. {\it Biometrika}, {\bf 65}, 581-590.
\reff{Lindley, D. V. (1964)} The Bayesian analysis of contingency tables.
{\it Annals of Mathematical Statistics}, {\bf 35}, 1622-1643.
\reff{Madigan, D. and Raftery, A.E. (1994)} Model selection and accounting
for model uncertainty in graphical models using Occam's window.
{\it Journal of the American Statistical Association} {\bf 89}, 1535-1546.
\reff{Madigan and York (1995)} Bayesian graphical models for discrete data.
{\it International Statistical Review}, {\bf 63}, 215-232.
\reff{Nazaret, W. A. (1987)} Bayesian log-linear estimates for three-way
contingency tables. {\it Biometrika}, {\bf 74}, 401-410.
\reff{Raftery, A. E. (1986)} A note on Bayes factors for log-linear
contingency table models with vague prior information. {\it
J. R. Statist. Soc. B}, {\bf 48},
\reff{Raftery, A. E. (1993)} Approximate Bayes factors and accounting for
model uncertainty in generalised linear models. Technical Report 255,
Department of Statistics, University of Washington.
\reff{Raftery, A. E. (1994)} Bayesian model selection in social research.
Technical report.
\reff{Raftery, A. E. and Richardson, S. (1996)} Model selection for
generalized linear models via GLIB, with application to nutrition and breast
cancer. In {\it Bayesian Biostatistics}, (eds. D. A. Berry and D. K.
Stangl), Marcel Dekker, New York, 321-353.
\reff{Spiegelhalter, D.J., and Smith, A.F.M. (1982)} Bayes factors for
linear and log-linear models with vague prior information. {\it Journal of
the Royal Statistical Society B}, {\bf 44}, 377-387.
\reff{Tierney, L. and Kadane, J.B. (1986)} Accurate Approximations for
Posterior Moments and Marginal Densities {\it Journal of the American
Statistical Association} {\bf 81}, 82-86.
\end{document}
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per informazioni rivolgersi a:
Renata Rotondi
Istituto per le Applicazioni della Matematica e dell'Informatica
Via Ampere, 56
20131 Milano
reni@iami.mi.cnr.it
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