Zorych, I., Madigan, D., Ryan, P., and Bate, A. (2011).
Disproportionality methods for pharmacovigilance in longitudinal observational databases. Submitted.

Madigan, D. and Ryan, P. (2011).
What can we really learn from observational studies? The need for empirical
assessment of methodology for active drug safety surveillance and comparative
effectiveness research. Submitted.

Madigan, D., Simpson, S., Hua, W., Paredes, A., Fireman, B., and Maclure, M. (2011).
The self-controlled case series: Recent developments. Submitted.

Madigan, D., Hauben, M., Vallarino, C., Patadia, V., Gerrits, C., and Simpson, S. (2011). The self-controlled case series method applied to a claims database for detection of signals in pharmacovigilance: A pilot study. Submitted.

Madigan, D., Ryan, P., Simpson, S.E., and Zorych, I. (2010).
Bayesian methods in pharmacovigilance (with discussion). In: J. M. Bernardo, M. J. Bayarri, J. O. Berger, A. P. Dawid, D. Heckerman, A. F. M. Smith and M. West (eds), *Bayesian Statistics 9*, Oxford University Press, to appear.

McCormick,
T., Rudin, C., and Madigan, D. (2010). A hierarchical model for association rule mining of sequential events: An approach to automated medical symptom prediction. Submitted.

Rudin, C.,
Salleb-Aouissi, A., Kogan, E. and Madigan, D. (2010). Ranking association rules
for recommender systems. Submitted.

McCormick,
T., Madigan, D., Raftery, A.E., and Burd, R.S. (2010). Dynamic model averaging
for logistic regression. Under revision at *Biometrics*.

Balakrishnan,
S. and Madigan, D. (2010). Priors on the variance in sparse Bayesian learning:
the demi-Bayesian lasso. In: Frontiers of Statistical Decision Making and
Bayesian Analysis: In Honor of James O. Berger by Ming-Hui Chen, Peter Muller,
Dongchu Sun, and Keying Ye.

Caster, O.,
Noren, G.N., Madigan, D., and Bate, A. (2010). Large-Scale Regression-Based
Pattern Discovery: The Example of Screening the WHO Global Drug Safety Database.
*Statistical Analysis and Data Mining, ***3**, 197-208.

Ross, J.S.,
Madigan, D., Konstam, M.A., Egilman, D.S., and Krumholz, H.M. (2010).
Does
Rofecoxib cardiovascular risk persist after discontinuation? *Archives of Internal Medicine*, **170**, 2035-2036.

Ross, J.S.,
Madigan, D., Hill, K.P., Egilman, D.S., Wang, Y., Krumholz, H.M. (2009). Pooled
analysis of Rofecoxib placebo-controlled clinical trial data: Lessons for
post-market pharmaceutical safety surveillance. *Archives of Internal Medicine*, **169**,
1976-1985.

Burd, R. and
Madigan, D. (2009). An evaluation of the impact of injury coding schemes on
mortality prediction in pediatric trauma. *Academic
Emergency Medicine*, **16**, 639-645.

Pearson,
R.K., Hauben, M., Goldsmith, D., Gould, A.L., Madigan, D., OHara, D.J.,
Reisinger, S., and Hochberg, A. (2009). Influence of the MEDDRA hierarchy on
pharmacovigilance data mining results. *International
Journal of Medical Informatics*, to appear.

Hochberg,
A., Hauben, M., Pearson, R.K., OHara, D., Reisinger, S., Goldsmith, D.I.,
Gould, A.L., and Madigan, D. (2009). An Evaluation of Three Signal Detection
Algorithms Using a Highly Inclusive Reference Event Database. *Drug Safety*, 32, 509-525.

Madigan, D. and Gelman, A. (2009). Discussion
of "What is statistics," by Emery Brown and Robert Kass,
*American Statistician*, 63, 114.

Madigan, D.,
Mittal, S., and Roberts, F. (2008). Efficient sequential decision making
algorithms for for container inspection operations. Under revision at *Naval Research Logistics.*

Burd, R.S.,
Ouyang, M., and Madigan, D. (2008). Bayesian logistic injury severity score
(BLISS): A method for predicting mortality using ICD-9 codes. *Academic Emergency Medicine*, 15(5),
466-475.

Caster, O.,
Noren, G.N., Madigan, D., and Bate, A. (2008). Large-scale regression-based
pattern discovery: The example of the WHO drug safety database. *KDD Workshop on Mining Medical Data, *to
appear.

Naik, P.,
Wedel, M., Bacon, L., Bodapati, A., Bradlow, E., Kamakura, W., Kreulen, J.,
Lenk, P., Madigan, D., and Montgomery, A. (2008). Challenges and Opportunities
in High-Dimensional Choice Data Analysis.* Marketing
Letters*.

Balakrishnan,
S. and Madigan, D. (2007). Algorithms for Sparse Linear Classifiers in the
Massive Data Setting. *Journal of Machine
Learning Research, ***9**, 313-337,
2007.

Balakrishnan,
S. and Madigan, D. (2007). LAPS:
Lasso with Partition Search. *Proceedings of the IEEE International
Conference on Data Mining,* 415-420.

Hauben, M.,
Madigan, D., Reisinger, S., Hochberg, A., and OHara, D. (2007). Data Mining in
Pharmacovigilence: Computational Cost as a Neglected Performance Parameter. *International Journal of Pharmaceutical
Medicine*, **21**, 319-323.

Hauben, M.,
Reich, L., Gerrits, C.M., and Madigan, D. (2007). Spontaneous Reporting of
Hyperkalemia and The Randomized Aldactone Evaluation Study. *Drug Safety*, **30**, 1143-1149.

Eyheramendy,
D. and Madigan, D. (2007). A
Bayesian feature selection score based on Naive
Bayes models. In: *Computational Methods
of Feature Selection*, H. Liu and H. Motoda, Editors, 277-294.

Madigan, D.,
Mittal, S., and Roberts, F. (2007). Sequential decision making algorithms for
port of entry inspection: overcoming computational challenges. *Proceedings of 2007 Intelligence and
Security Informatics Conference*, 1-7.

Rolka, H.,
Burkom, H., Cooper, G.F., Kulldorff, M., Madigan, D., and Wong, W-K. (2006).
Issues in Applied Statistics for Public Health Bioterrorism Surveillance using
Multiple Data Streams: Research needs. *Statistics
in Medicine*, **26**, 1834-1856.

Eyheramendy,
S. and Madigan, D. (2007). A Flexible Bayesian Generalized Linear Model for
Dichotomous Response Data with an Application to Text Categorization. In: IMS Lecture
Notes - Monograph Series, Volume 54, *Complex
datasets and inverse problems: tomography, networks and beyond*. Regina Liu,
William Strawderman & Cun-Hui Zhang, Editors, 76-91.

Balakrishnan,
S. and Madigan, D. (2006). Decision Trees for Functional Variables. *Proceedings of the IEEE International
Conference on Data Mining,* 798-802.

Genkin, A.,
Lewis, D.D., and Madigan, D. (2007). Large-scale Bayesian logistic regression
for text categorization. *Technometrics*,
**49**, 291-304.

Dayanik, A.,
Lewis, D.D., Madigan, D., Menkov, V., and Genkin, A. (2006). Constructing
Informative Prior Distributions from Domain Knowledge in Text Classification, *Proceedings of the 29 ^{th} Annual
International ACM SIGIR conference*, 493-500.

Anand, S.,
Madigan, D., Mammone, R., Pathak, S. and Roberts, F. (2006). Experimental
Analysis of Sequential Decision Making Algorithms for Port of Entry Inspection
Procedures. In S. Mehrotra, D. Zeng, H. Chen, B. Thuraisingham, and F-X Wang
(eds.), Intelligence and Security Informatics, *Proceedings of ISI-2006, Lecture Notes in Computer Science #3975,*
Springer-Verlag, New York, 2006.

Balakrishnan,
S. and Madigan, D. (2006). A One-Pass Sequential Monte Carlo Method for
Bayesian Analysis of Massive Datasets. *Bayesian
Analysis*. **1**, 345-362.

Madigan, D.,
Ju, W., Krishnan, P., and Krishnakumar, A.S. (2006). Location estimation in
wireless networks: A Bayesian approach. *Statistica
Sinica*, 16, 495-522.

Madigan, D.,
Vardi, Y., and Weissman, I. (2006). Extreme value theory applied to document
retrieval from large collections. *Information
Retrieval*, **9**, 273-294.

Hauben, M.,
Madigan, D., Gerrits, C., and Meyboom, R. (2005). The role of data mining in
pharmacovigilance. *Expert Opinion in Drug
Safety*., **4**(5), 929-948.

Madigan, D.,
Genkin, A., Lewis, D.D., and Fradkin, D. (2005). Bayesian multinomial logistic regression
for author identification. *Proceedings of
the 25 ^{th} International Workshop on Bayesian inference and Maximum
Entropy Methods in Science and Engineering (MaxEnt 05)*, 509-516.

Madigan, D.,
Genkin, A., Argamon, S., Fradkin, D., and Ye, L. (2005). Author identification.
*Proceedings of CSNA/Interface 05*.

Eyheramendy,
S. and Madigan, D. (2005). A Novel Feature Selection Score for Text
Categorization. *International Workshop on
Feature Selection for Data Mining*, 1-8.

Madigan, D.
(2005). Statistics and Data Mining. In: *AMS-DIMACS
Discrete Methods in Epidemiology*, James Abello and Graham Cormode
(Editors), 21-24.

Hanks, S.
and Madigan, D. (2005). Probabilistic temporal reasoning. In: *Handbook of Temporal Reasoning in Artificial
Intelligence*, M. Fisher, D. Gabbay, and L. Vila, Editors, Elsevier B.V.,
315-342.

Madigan, D.,
Elnahrawy, E., Martin, R.P., Ju, W., Krishnan, P. and Krishnakumar, A.S. (2004).
Bayesian Indoor Positioning Systems. *Proceedings
of IEEE Infocom*, 1217-1227.

Madigan, D.
(2005). Bayesian data mining for surveillance. In: *Spatial and Syndromic Surveillance for Public Health* (Andrew Lawson
and Ken Kleinman, Editors), 203-221.

Madigan, D.
(2004). Statistics and the war on spam. In: *Statistics:
A Guide to the Unknown*, Deb Nolan (Editor), 135-147.

Madigan, D.
and Stuetzle, W. (2004). Graduate statistics education (discussion of A Report on the Future of Statistics).
*
Statistical Science*, **19**,
408-409.

Fradkin, D.
and Madigan, D. (2003). Experiments with random projections for machine
learning. In *Proceedings of KDD-03, The
Ninth International Conference on Knowledge Discovery and Data Mining*,
517-522.

Ridgeway, G.
and Madigan, D. (2003). A sequential Monte Carlo Method for Bayesian analysis
of massive datasets. *Journal of Knowledge
Discovery and Data Mining*, **7**,
301-319.** **

Eyheramendy,
S., Lewis, David D., and Madigan, David (2003). On the naive bayes model for
text classification. In *Proceedings of
The Ninth International Workshop on Artificial Intelligence and Statistics*,
C.M. Bishop and B.J. Frey (Editors), 332-339.

Madigan, D.,
Vardi, Y., and Weissman, I. (2003). On retrieval properties of samples of large
collections. In *Proceedings of The Ninth
International Workshop on Artificial Intelligence and Statistics*, C.M.
Bishop and B.J. Frey (Editors), 265-270.

Madigan, D.
and Ridgeway, G. (2003). Bayesian data analysis for data mining. In *Handbook
of Data Mining*, N. Ye (Ed.), 103-132..

Cohen, A.,
Madigan, D., and Sackrowitz, H.B. (2003). Effective directed tests for models
with ordered categorical data. *Australian
and New Zealand Journal of Statistics*, **45**,
285-200. 2003 Best Paper Award.

Mangione,
S., Yuen, E., and Madigan, D. (2003). Asthma in Philadelphia schools. *Chest*, **124** (4): 141S.

Mangione,
S., Yuen, E., and Madigan, D. (2003). Asthma and tobacco: A survey of 65 Philadelphia
middle schools. *Chest*, **124** (4): 141S-142S.

Dunbar,
P.J., Madigan, D., Grohskopf, L.A., Revere, D., Woodward, J., Minstrell, J.,
Frick, P.A., Simoni, J.M., and Hooton, T.M. (2003). A two-way messaging system
to enhance antiretroviral adherence. *Journal
of The American Medical Informatics Association*, **10**, 11-15.

Ridgeway, G.
and Madigan, D. (2002). Bayesian analysis of massive datasets via particle
filters In *Proceedings of KDD-02, The Eighth International Conference on Knowledge
Discovery and Data Mining*, 5-13.

Madigan, D.,
Raghavan, N., DuMouchel, W., Nason, M., Posse, C., and Ridgeway, G. (2002).
Likelihood-based data squashing: A modeling approach to instance construction. *Journal of Data Mining and Knowledge
Discovery*, **6**, 173-190.

Tanimoto,
S., Carlson, A., Husted, J., Hunt, E.B., Larsson, J., Madigan, D., and
Minstrell, J. (2002). Text Forum Features for Small Group Discussions with
Facet-Based Pedagogy. *Proceedings of
CSCL2002, Computer Supported Cooperative Learning*.

Hoeting, J.,
Raftery, A.E., and Madigan, D. (2002). Amethod for simultaneous variable and
transformation selection in linear regression. *Journal of Computational and Graphical Statistics*, **11**, 485-507.

Liu, R.,
Madigan, D., and Eyheramendy, S. (2002).
Text classification for mining
aviation inspection reports. In: *Statistical
Data Analysis based on the L1-norm and Related methods*. Birkhauser
Statistics for Industry and technology, Y. Dodge editor, 379-392.

da Silva,
C.Q., Zeh, J., Madigan, D., Laake, J., Rugh, D., Baraff, L., Koski, W., and
Miller, G. (2001). Capture-recapture estimation of bowhead whale population
size estimation using photo-identification data.* Journal of Cetacean Research and Management*, **2**, 45-61.

Levitz, M.,
Perlman, M.D., and Madigan, D. (2001). Separation and Completeness Properties
for AMP Chain Graph Markov Models. *Annals
of Statistics*, **29**,
1751–1784.

Church, L.,
Oliver, L., Dobie, S., Madigan, D., and Ellsworth, A. (2001). Analgesia for
colposcopy: A double-blind, randomized comparison of ibuprofen and benzocaine
gel for colposcopic analgesia. *Obstetrics
and Gynecology*,**97**, 5-10.

Andersson,
S.A., Madigan, D., and Perlman, M.D. (2001). An alternative Markov property for
chain graphs. *Scandinavian Journal of
Statistics*, **28**, 33-85.

Glusker,
A.I., Dobie, S.A., Madigan, D., Rosenblatt, R.A., Larson, E.H. (2000).
Differences in fertility patterns between urban and rural women in Washington
state, 1983-1984 to 1993-1994. *Women and
Health,*** 31**, 55-70.

Kanungo, T.,
Haralick, R. M., Baird, H. Stuetzle, W., and Madigan, D. (2000). A statistical,
nonparametric methodology for document degradation models validation. *IEEE Transactions on Pattern Analysis and
Machine Intelligence*, **22**,
1209-1223.

Dobie, S.A.,
Hart, G., Glusker, A., Rosenblatt, R., and Madigan, D. (2000). Reproductive
health services in rural Washington state: Scope of practice and the potential
of medical abortions. *American Journal of
Public Health*., **90**, 624-626.

Madigan, D.
and Nason, M. (2000). Statistics perspectives on data and knowledge. *Handbook of Knowledge Discovery and Data
Mining*, Oxford University Press.

Nason, M.
and Madigan, D. (2000). Sampling. *Handbook
of Knowledge Discovery and Data Mining*, Oxford University Press.

Madigan, D.,
Raghavan, N., DuMouchel, W., Nason, M., Posse, C., and Ridgeway, G. (2000).
Instance construction via likelihood-based data squashing. *Instance Selection and Construction, A Data Mining Perspective*, H.
Motoda and H. Liu (Eds.), Kluwer, 209-226.

Hoeting,
J.A., Madigan, D., Raftery, A.E.,
and Volinsky, C.T. (1999). Bayesian model averaging - a tutorial. *Statistical Science*, **14**, 382-401.

Dobie, S.A.,
Hart, G., Glusker, A., Madigan, D., Larsen, E.B., and Rosenblatt, R. (1999).
Abortion services in rural Washington State, 1983-1984 to 1993-1994:
availability and outcomes. *Family
Planning Perspectives*, **31**,
241-245.

Condliff,
M.K., Lewis, D.D., Madigan, D., and Posse, C. (1999). Bayesian mixed-effects
models for recommender systems. *Proceedings
of SIGIR-99 Workshop on Recommender Systems*.

Madigan, D.
(1999). Bayesian Graphical Models, Intention-to-Treat, and the Rubin Causal
Model. In *Proceedings of Uncertainty-99,
The Seventh International Workshop on Artificial Intelligence and Statistics*,
123-132.

Golinelli,
D., Madigan, D., and Consonni, G. (1999). Relaxing the local independence
assumption for quantitative learning in acyclic directed graphical models
through hierarchical partition models. In *Proceedings
of Uncertainty-99, The Seventh International Workshop on Artificial
Intelligence and Statistics*, 203-208.

Ridgeway,
G., Madigan, D., and Richardson, T. (1999). Boosting Methodology for Regression
Problems. In *Proceedings of
Uncertainty-99, The Seventh International Workshop on Artificial Intelligence
and Statistics*, 152-161.

Ridgeway,
G., Madigan, D., Richardson, T., and O'Kane, K. (1998). Interpretable Boosted
Naive Bayes Classification In *Proceedings of KDD-98, The Fourth
International Conference on Knowledge Discovery and Data Mining*, 101-104.

Andersson,
S.A., Madigan, D., Perlman, M.D., and Richardson, T. (1998). Graphical Markov
Models in multivariate analysis. In *Multivariate
Analysis, Design of Experiments, and Survey Sampling*, Subir Ghosh (Ed.), Marcel Dekker Inc.

Draper, D.
and Madigan, D. (1997). The scientific value of Bayesian statistical methods. *IEEE Intelligent Systems and their
Applications*, **12**, 18-21.

Madigan, D.
and York, J. (1997). Bayesian methods for estimating the size of a closed
population. *Biometrika*, **84**, 19-31.

Glymour, C.,
Madigan, D., Pregibon, D., and Smyth, P. (1997). Statistical themes and lessons
for data mining. *Journal of Data Mining
and Knowledge Discovery*, **1**,
11-28.

Volinsky,
C.T., Madigan, D., Raftery, A.E., and Kronmal, R.A. (1997). Bayesian Model
Averaging in Proportional Hazard Models: Predicting Strokes. *Applied Statistics ***46**, 433-448.

Andersson,
S.A., Madigan, D., Perlman, M.D., and Triggs, C.M. (1997). A graphical
characterization of lattice conditional independence models. *Annals of Mathematics and Artificial
Intelligence*, **21**, 27-50.

Madigan, D.,
Mosurski, K., and Almond, R.G. (1997). Explanation in belief networks. *Journal of Computational and Graphical
Statistics*, **6**, 160-181.

Andersson,
S.A., Madigan, D., and Perlman, M.D., (1997). A characterization of Markov
equivalence classes for acyclic digraphs. *Annals
of Statistics*, **25**, 505-541.

Raftery,
A.E., Madigan, D., and Hoeting, J. (1997). Accounting for model uncertainty in
linear regression. *Journal of the
American Statistical Association*, **92**,
179-191.

Madigan, D.,
Keim, M, and Lewis, D.D. (1997). Bayesian information retrieval. *Proceedings of the Sixth International
Workshop on Artificial Intelligence and Statistics*, 303-310.

Andersson,
S.A., Madigan, D., and Perlman, M.D. (1997). On the Markov equivalence of chain
graphs, undirected graphs, and acyclic digraphs. *Scandinavian Journal of Statistics*, **24**, 81-102.

Madigan, D.,
Raftery, A.E., Volinsky, C.T., and Hoeting, J.A. (1996). Bayesian model
averaging. In*: Integrating Mulitple
Learned Models (IMLM-96)*, P. Chan, S. Stolfo, and D. Wolpert (Eds.), 77-83.

Raftery,
A.E., Madigan, D., and Volinsky, C.T. (1996). Accounting for model uncertainty
in survival analysis improves predictive performance. In: Bernardo, J. M.,
Berger, J. O., Dawid, A. P. and Smith A. F. M., (eds.), *Bayesian Statistics V*, Oxford University Press, 323-350.

Andersson,
S.A., Madigan, D., and Perlman, M.D. (1996). An alternative Markov property for
chain graphs. In *Proceedings of the
Twelfth Annual Conference on Uncertainty in Artificial Intelligence*, Eric Horvitz and Finn Jensen (Eds.),
Morgan Kaufmann Publishers, Inc., San Mateo.

Schaffner,
A., Madigan, D., Hunt, E., Graf, E., Minstrell, J., and Nason, M. (1996).
Benchmark lessons and the world wide web: Tools for teaching statistics. In: D.
Edelson and E. Domeshek (Eds.) *Proceedings
of ICLS 96. Association for the Advancement of Computing in Education, *480-484.

Madigan, D.
and Almond, R.G. (1996). On test selection strategies for belief networks. In *Learning from Data: Artificial Intelligence
and Statistics V*, D. D. Fisher and H. Lenz (Eds.), Springer Verlag, 89-98.

Glymour, C.,
Madigan, D., Pregibon, D., and Smyth, P., and (1996). Statistical inference and
data mining. *Communications of the ACM*,
**39**, 35-41.

Madigan, D.,
Andersson, S.A., Perlman, M.D, and Volinsky, C.T. (1996). Bayesian model
averaging and model selection for Markov equivalence classes of acyclic
digraphs. *Communications in Statistics -
Theory and Methods*, **25**,
2493-2519.

Hoeting,
J.A., Madigan, D., and Raftery, A.E. (1996). A Method for Simultaneous Variable
Selection and Outlier Identification in Linear Regression, *Journal of Computational Statistics and Data Analysis*, **22**, 251-270.

Madigan, D.,
Chapman, C.R., Gavrin, J., Villumsen, O., and Boose, J.H. (1995). Repertory
hypergrids for large-scale hypermedia linking. *International Journal of Human-Computer Studies*, 43, 465-481.

Madigan, D.,
Gavrin, J., and Raftery, A.E. (1995). Eliciting prior information to enhance
the predictive performance of Bayesian graphical models. *Communications in Statistics - Theory and Methods*, 24, 2271-2292.

Madigan, D.
and York, J. (1995). Bayesian graphical models for discrete data. *International
Statistical Review*, 63, 215-232.

Andersson,
S.A., Madigan, D., Perlman, M.D., and Triggs, C.M., (1995). On the relation
between conditional independence models determined by finite distributive
lattices and by directed acyclic graphs. *Journal
of Statistical Planning and Inference, ***46**,
25-46.

York, J.,
Madigan, D., Heuch, I., and Lie, R.T. (1995). Estimation of the proportion of
congenital malformations using double sampling: Incorporating covariates and
accounting for model uncertainty. *Applied
Statistics*, **44**, 227–242.

Madigan, D.,
and Chapman, C.R. (1995). Multimedia tools for cancer pain education. In: *Medical Multimedia*, C. Ghaoui and R.
Rada (Eds.), Intellect, Oxford, 121–136.

Haynor, D.
and Madigan, D. (1995). Bayesian approach to differential diagnosis with use of
Monte Carlo technique. *Radiology*, **197**, 425S.

Hanks, S.,
Madigan, D., and Gavrin, J. (1995). Temporal reasoning in probabilistic
knowledge-based systems. In *Proceedings
of the Eleventh Annual Conference on Uncertainty in Artificial Intelligence*, Philippe Besnard and Steve Hanks (Eds.),
Morgan Kaufmann Publishers, Inc., San Mateo, 111-119.

Madigan, D.,
Chapman, C.R., Gavrin, J., Villumsen, O., and Boose, J.H. (1994). Repertory
Hypergrids: An Application to Clinical Practice Guidelines. *Proceedings of the ACM European Conference on
Hypermedia Technology*, 117–125.

Almond, R,
Bradshaw, J.M., and Madigan, D. (1994). Reuse and sharing of graphical belief
network components. In *Selecting Models
from Data: Artificial Intelligence and Statistics IV*, P. Cheeseman and W.
Oldford (Eds.), Springer Verlag, 113-122.

Madigan, D.,
York, J.C., Bradshaw, J.M., and Almond, R.G. (1994). Bayesian graphical models for
predicting errors in databases. In *Selecting
Models from Data: Artificial Intelligence and Statistics IV*, P. Cheeseman
and W. Oldford (Eds.), Springer Verlag, 123-132.

Madigan, D.,
Raftery, A.E., York, J.C., Bradshaw, J.M., and Almond, R.G. (1994). Strategies
for graphical model selection. In *Selecting
Models from Data: Artificial Intelligence and Statistics IV*, P. Cheeseman
and W. Oldford (Eds.), Springer Verlag, 91-100.

York, J.C.
and Madigan, D. (1994). Markov chain Monte Carlo methods for hierarchical
Bayesian expert systems. In *Selecting
Models from Data: Artificial Intelligence and Statistics IV*, P. Cheeseman
and W. Oldford (Eds.), Springer Verlag.

Madigan, D.,
Chapman, C.R., Gavrin, J., Villumsen, O., and Boose, J.H. (1994). Modularized
Maintenance for Hyperlinking: An Application to Clinical Practice Guidelines. *Proceedings of the AAAI-94 Workshop on
Indexing and Reuse in Multimedia Systems*, 126–140.

Kanungo, T.,
Haralick, R. M., Stuetzle, W., and Madigan, D. (1994). Document Degradation
Models: Parameter Estimation and model validation. In *Proc. of Int. Workshop on Machine Vision Applications*, Kawasaki,
Japan, 552-557.

Madigan, D.
and Raftery, A.E. (1994). Model Selection and accounting for model uncertainty
in graphical models using Occam's window. *Journal
of the American Statistical Association*, **89**, 1535–1546.

Madigan, D.
(1993). A note on equivalence classes of directed acyclic independence graphs. *Probability in the Engineering and
Informational Sciences*, **7**:
409–412.

Bradshaw,
J.M., Chapman, C.R., Sullivan, K.M., Almond, R.G., Madigan, D., Zarley, D.,
Gavrin, J., Nims, J., and Bush, N. (1993). KS-3000: Applying DDUCKS to
bone-marrow transplant patient support. *Proceedings
of the Sixth Annual Florida AI Research Symposium (FLAIRS '93)*, Ft. Lauderdale,
FL, April, 78–83.

Bradshaw,
J.M., Madigan, D., Richards, T., and Boy, G.A. (1993). Emerging technology and
concepts for computer-based training. *Proceedings
of the Sixth Annual Florida AI Research Symposium (FLAIRS '93)*, Ft.
Lauderdale, FL, April, 89–95.

Bradshaw,
J.M., Richards, T., Fairweather, P., Buchanan, C., Guay, R., Madigan, D.,and
Boy, G.A. (1993). New directions in
computer-based training in aerospace.
*Proceedings of the Fourth
International Conference on Human Machine Interactions and Artificial
Intelligence in Aerospace*. Toulouse, France.

Bradshaw,
J.M., Chapman, C.R., Sullivan, K.M., Boose, J.H., Almond, R.G., Madigan, D.,
Zarley, D., Gavrin, J., Nims, J. and Bush, N. (1993). KS-3000: An application
of DDUCKS to bone-marrow transplant patient support*. Proceedings of the Seventh European Knowledge Acquisition for
Knowledge-Based Systems Workshop (EKAW-93)*. Toulouse and Caylus, France,
57-74.

E.A. Kiely,
Madigan, D., P.C. Ryan and M.R. Butler (1991). Ultrasonic imaging for
extracorporeal shockwave lithotripsy: Analysis of factors in successful
treatment. *British Journal of Urology*,
**66**: 127–131.

Madigan, D.
and Mosurski, K. (1991). An extension of the results of Asmussen and Edwards on
collapsibility in contingency tables. *Biometrika*,
**77**: 315–319 (Correction).

Pickering,
W.H., Madigan, D., McCarter, R.J., and Burd, R.S. (2009). Evaluating relative
importance of injury groupings on in-hospital mortality.

Cheng, J.
and Madigan, D. (2008). Bayesian Approaches to Aspects of the Vioxx Trials:
Non-ignorable Dropout and Sequential Meta-Analysis. Submitted.

Hauben, M.,
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