David Madigan

A. S. Krishnakumar, Parameshwaran Krishnan, David Madigan, 2005, Proceedings IEEE 24th Annual Joint Conference of the IEEE Computer and Communications Societies..

Simultaneous Variable and Transformation Selection in Linear Regression

Adrian E. Raftery, David Madigan, Jennifer A. Hoeting, 1995 .

Challenges and opportunities in high-dimensional choice data analyses

Michel Wedel, Wagner A. Kamakura, Eric T. Bradlow, 2008 .

[A Report on the Future of Statistics]: Comment

David Madigan, Werner Stuetzle, 2004 .

Learning theory analysis for association rules and sequential event prediction

Cynthia Rudin, David Madigan, Benjamin Letham, 2013, J. Mach. Learn. Res..

Observational Health Data Sciences and Informatics (OHDSI): Opportunities for Observational Researchers

Yu-Chuan Li, George Hripcsak, Patrick B. Ryan, 2015, MedInfo.

Constructing informative prior distributions from domain knowledge in text classification

David Madigan, David D. Lewis, Aynur A. Dayanik, 2006, SIGIR.

An Interpretable Stroke Prediction Model using Rules and Bayesian Analysis

Cynthia Rudin, David Madigan, Benjamin Letham, 2013, AAAI.

Statistics and The War on Spam

David Madigan, 2003 .

Large-scale evidence generation and evaluation across a network of databases (LEGEND): assessing validity using hypertension as a case study

George Hripcsak, David Madigan, Martijn J Schuemie, 2020, J. Am. Medical Informatics Assoc..

Dynamic Logistic Regression and Dynamic Model Averaging for Binary Classification

David Madigan, Tyler H McCormick, Adrian E Raftery, 2012, Biometrics.

Discussion on the paper by Friedman and Fisher

Thomas Richardson, David Madigan, Greg Ridgeway, 1999, Stat. Comput..

Efficient sequential decision‐making algorithms for container inspection operations

Fred S. Roberts, David Madigan, Sushil Mittal, 2011 .

Bayesian Graphical Models for Predicting Errors in Databases

Russell G. Almond, Jeffrey M. Bradshaw, David Madigan, 1994 .

Experimental Analysis of Sequential Decision Making Algorithms for Port of Entry Inspection Procedures

Fred S. Roberts, Richard J. Mammone, David Madigan, 2006, ISI.

Text forum features for small group discussions with facet-based pedagogy

Adam Carlson, Steven L. Tanimoto, David Madigan, 2002, CSCL.

Probabilistic Temporal Reasoning with Endogenous Change pdf

David Madigan, Steve Hanks, Jonathan Gavrin, 1995, UAI.

Editorial

David Madigan, 2014, Stat. Anal. Data Min..

Response to comment on 'empirical assessment of methods for risk identification in healthcare data'.

David Madigan, Patrick B Ryan, Paul E Stang, 2013, Statistics in medicine.

The scientific value of Bayesian statistical methods

David Madigan, David Draper, 1997 .

Text Classification for Mining Massive Aviation Inspection Reports

David Madigan, Regina Y. Liu, Susana Eyheramendy, 2002 .

Finding Predictive Runs with LAPS

David Madigan, Suhrid Balakrishnan, 2007, Seventh IEEE International Conference on Data Mining (ICDM 2007).

Interpretable classifiers using rules and Bayesian analysis: Building a better stroke prediction model pdf

Cynthia Rudin, David Madigan, Benjamin Letham, 2015, ArXiv.

A graphical characterization of lattice conditional independence models

David Madigan, Christopher M. Triggs, Michael D. Perlman, 2004, Annals of Mathematics and Artificial Intelligence.

The Electronic Hard Hat: CSCW on the Construction Site

David Madigan, 1996 .

An Alternative Markov Property for Chain Graphs

David Madigan, Michael D. Perlman, Steen A. Andersson, 1996, UAI.

Interpretable Boosted Naïve Bayes Classification

Thomas Richardson, David Madigan, Greg Ridgeway, 1998, KDD.

Bayesian Hierarchical Rule Modeling for Predicting Medical Conditions

Cynthia Rudin, David Madigan, Tyler H. McCormick, 2012 .

Stable discovery of interpretable subgroups via calibration in causal studies pdf

David Madigan, Raaz Dwivedi, Kevin Horgan, 2020, ArXiv.

Experiments with random projections for machine learning

Dmitriy Fradkin, David Madigan, D. Madigan, 2003, KDD '03.

Intelligence and Security Informatics: Biosurveillance, Second NSF Workshop, BioSurveillance 2007, New Brunswick, NJ, USA, May 22, 2007, Proceedings

Hsinchun Chen, Daniel Zeng, David Madigan, 2007, BioSurveillance.

Likelihood-Based Data Squashing: A Modeling Approach to Instance Construction

Christian Posse, William DuMouchel, David Madigan, 2002, Data Mining and Knowledge Discovery.

Bayesian Methods in Pharmacovigilance

David Madigan, Ivan Zorych, Patrick Ryan, 2010 .

Influence of the MedDRA® hierarchy on pharmacovigilance data mining results

David Madigan, Manfred Hauben, Stephanie J. Reisinger, 2009, Int. J. Medical Informatics.

Relaxing the local independence assumption for quantitative learning in acyclic directed graphical models through hierarchical partition models

David Madigan, Guido Consonni, Daniela Golinelli, 1999, AISTATS.

On Retrieval Properties of Samples of Large Collections

David Madigan, Yehuda Vardi, Ishay Weissman, 2003, AISTATS.

Bayesian Model Averaging

Adrian E. Raftery, David Madigan, Chris T. Volinsky, 1998 .

The Factorized Self-Controlled Case Series Method: An Approach for Estimating the Effects of Many Drugs on Many Outcomes

Cynthia Rudin, David Madigan, Ramin Moghaddass, 2016, J. Mach. Learn. Res..

Large-scale regression-based pattern discovery: The example of screening the WHO global drug safety database

David Madigan, G. Niklas Norén, Andrew Bate, 2010 .

Large‐scale regression‐based pattern discovery: The example of screening the WHO global drug safety database

David Madigan, G. Niklas Norén, Andrew Bate, 2010, Stat. Anal. Data Min..

Bayesian graphical models, intention-to-treat, and the rubin causal Model

David Madigan, D. Madigan, 1999, AISTATS.

Predicting health outcomes from high-dimensional longitudinal health histories using relational random forests

Patrick B. Ryan, David Madigan, Zach Shahn, 2015, Stat. Anal. Data Min..

Author Identification on the Large Scale

Shlomo Argamon, Dmitriy Fradkin, David Madigan, 2005 .

A Bayesian Feature Selection Score Based on Naïve Bayes Models

David Madigan, Susana Eyheramendy, D. Madigan, 2007 .

Priors on the Variance in Sparse Bayesian Learning; the demi-Bayesian Lasso

David Madigan, D. Madigan, 2008 .

Statistical Themes and Lessons for Data Mining

Padhraic Smyth, Clark Glymour, David Madigan, 2004, Data Mining and Knowledge Discovery.

Reuse and sharing of graphical belief network components

Russell G. Almond, Jeffrey M. Bradshaw, David Madigan, 1994 .

Improving reproducibility by using high-throughput observational studies with empirical calibration

George Hripcsak, David Madigan, Martijn J Schuemie, 2018, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

Sequential event prediction

Cynthia Rudin, David Madigan, Benjamin Letham, 2013, Machine Learning.

Statistical inference and data mining : Data mining and knowledge discovery in databases

Padhraic Smyth, Clark Glymour, David Madigan, 1996 .

Generalization of boosting algorithms and applications of bayesian inference for massive datasets

Thomas S. Richardson, David Madigan, Gregory Kirk Ridgeway, 1999 .

Strategies for Graphical Model Selection

Russell G. Almond, Jeffrey M. Bradshaw, Adrian E. Raftery, 1994 .

Extreme value theory applied to document retrieval from large collections

David Madigan, Yehuda Vardi, Ishay Weissman, 2006, Information Retrieval.

Bayesian model averaging: a tutorial (with comments by M. Clyde, David Draper and E. I. George, and a rejoinder by the authors

Adrian E. Raftery, Chris Volinsky, David Madigan, 1999 .

Bayesian Multinomial Logistic Regression for Author Identification

Dmitriy Fradkin, David Madigan, David Lewis, 2005, AIP Conference Proceedings.

Issues in applied statistics for public health bioterrorism surveillance using multiple data streams: research needs

Gregory F Cooper, Weng-Keen Wong, David Madigan, 2007, Statistics in medicine.

Proceedings of the Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, San Diego, CA, USA, August 15-18, 1999

Surajit Chaudhuri, David Madigan, Usama M. Fayyad, 1999, KDD.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics): Preface

Hsinchun Chen, Daniel Zeng, David Madigan, 2007, KDD 2013.

Probabilistic Temporal Reasoning

David Madigan, Steve Hanks, S. Hanks, 2005, Handbook of Temporal Reasoning in Artificial Intelligence.

Bayesian Graphical Modeling for Intelligent Tutoring Systems

David Madigan, Earl Hunt, Deborah Donnell, 1994 .

DIMACS at the TREC 2004 Genomics Track

Paul B. Kantor, Dmitriy Fradkin, David Madigan, 2004, TREC.

Bayesian Data Analysis for Data Mining

David Madigan, Greg Ridgeway, D. Madigan, 2002 .

Proceedings of the 2011 workshop on Data mining for medicine and healthcare

Nitesh V. Chawla, Rayid Ghani, Jianying Hu, 2011, KDD 2011.

Graphical models in applied multivariate statistics, by J. Whittaker, John Wiley & Sons, New York, 1990, 448 pp. Price: $59.95

David Madigan, 1994, Networks.

Bayesian Mixed-Effects Models for Recommender Systems

Christian Posse, David Madigan, David Lewis, 1999 .

Enhancing the Predictive Performance of BayesianGraphical

Adrian E. Raftery, David Madigan, Denise Draper, 1995 .

Sequential Decision Making Algorithms for Port of Entry Inspection: Overcoming Computational Challenges

Fred S. Roberts, David Madigan, Sushil Mittal, 2007, 2007 IEEE Intelligence and Security Informatics.

Optimizing the leveraging of real-world data to improve the development and use of medicines.

David Madigan, Craig Lipset, Kirsten Axelsen, 2015, Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research.

Implementation Brief: A Two-way Messaging System to Enhance Antiretroviral Adherence

David Madigan, Debra Revere, James Minstrell, 2003, J. Am. Medical Informatics Assoc..

Benchmark lessons and the world wide web: tools for teaching statistics

Edith Aurora Graf, David Madigan, Earl Hunt, 1996 .

Bayesian analysis of massive datasets via particle filters

David Madigan, Greg Ridgeway, 2002, KDD.

DIMACS AT THE TREC 2004 GENOMICS TRACK (DRAFT)

Dmitriy Fradkin, David Madigan, David D. Lewis, 2004 .

Document Degradation Models: Parameter Estimation and Model Validation

Robert M. Haralick, Tapas Kanungo, David Madigan, 1994, MVA.

Bayesian hierarchical vector autoregressive models for patient-level predictive modeling

David Madigan, Feihan Lu, Yao Zheng, 2018, PloS one.

Boosting methodology for regression problems

Thomas Richardson, David Madigan, Greg Ridgeway, 1999, AISTATS.

On the Naive Bayes Model for Text Categorization

David Madigan, David D. Lewis, Susana Eyheramendy, 2003, AISTATS.

Large-Scale Regression-Based Pattern Discovery in International Adverse Drug Reaction Surveillance

David Madigan, G. Niklas Norén, Andrew Bate, 2008 .

Accounting for Model Uncertainty in Survival Analysis Improves Predictive Performance

Adrian E. Raftery, Chris Volinsky, David Madigan, 1995 .

DIMACS at the TREC 2005 Genomics Track

Paul B. Kantor, David Madigan, David D. Lewis, 2005, TREC.

Bayesian Hierarchical Rule Modeling for Predicting Medical Conditions

Cynthia Rudin, David Madigan, Tyler H. McCormick, 2012, 1206.6653.

Graphical Explanation in Belief Networks

Russell G. Almond, David Madigan, Krzysztof Mosurski, 1997 .

A Sequential Monte Carlo Method for Bayesian Analysis of Massive Datasets

David Madigan, Greg Ridgeway, D. Madigan, 2003, Data Mining and Knowledge Discovery.

Sequential Event Prediction with Association Rules

Cynthia Rudin, David Madigan, Benjamin Letham, 2011, COLT.

Editorial: knowledge-based hypermedia

David Madigan, 1995, Int. J. Hum. Comput. Stud..

Instance Construction via Likelihood-Based Data Squashing

Christian Posse, William DuMouchel, David Madigan, 2001 .

LOCATION ESTIMATION IN WIRELESS NETWORKS: A BAYESIAN APPROACH

Wen-Hua Ju, David Madigan, Ivan Zorych, 2006 .

Session details: Keynote Talk I

David Madigan, 2020 .

A Learning Theory Framework for Sequential Event Prediction and Association Rules

Cynthia Rudin, David Madigan, Benjamin Letham, 2012 .

Bayesian Model Averaging: A Tutorial

Adrian E. Raftery, Chris Volinsky, David Madigan, 2016 .

Multiple Self‐Controlled Case Series for Large‐Scale Longitudinal Observational Databases

David Madigan, Martijn J Schuemie, Marc A Suchard, 2013, Biometrics.

Large‐scale parametric survival analysis

David Madigan, Sushil Mittal, Randall S Burd, 2013, Statistics in medicine.

Piezo Actuated Flexural Stage for Sub-Micron Precision Measurement

David Madigan, D. Madigan, 2008 .

On Test Selection Strategies for Belief Networks

Russell G. Almond, David Madigan, D. Madigan, 1995, AISTATS.

Hierarchical models for multiple, rare outcomes using massive observational healthcare databases

Patrick B. Ryan, Martijn J. Schuemie, David Madigan, 2016, Stat. Anal. Data Min..

How Confident Are We about Observational Findings in Healthcare: A Benchmark Study.

George Hripcsak, Patrick B. Ryan, Martijn J. Schuemie, 2020, Harvard data science review.

Decision Trees for Functional Variables

David Madigan, Suhrid Balakrishnan, D. Madigan, 2006, Sixth International Conference on Data Mining (ICDM'06).

MODEL SELECTION AND ACCOUNTING FOR MODEL UNCERTAINTY IN LINEAR REGRESSION MODELS

Adrian E. Raftery, David Madigan, Jennifer A. Hoeting, 2007 .

Combining cox regressions across a heterogeneous distributed research network facing small and zero counts

David Madigan, Martijn J Schuemie, Marc A Suchard, 2021, Statistical methods in medical research.

Erratum to: Large-Scale Evidence Generation and Evaluation across a Network of Databases (LEGEND): Assessing Validity Using Hypertension as a Case Study

George Hripcsak, David Madigan, Martijn J Schuemie, 2021, J. Am. Medical Informatics Assoc..

Bayesian Methods for Estimating the Size of a Closed Population

David Madigan, Jeremy C. York, J. York, 1992 .

Self-Controlled Case Series 1 The Self-Controlled Case Series : Recent Developments

David Madigan, 2011 .

Persistence of cardiovascular risk after rofecoxib discontinuation.

David Madigan, Harlan M Krumholz, D. Madigan, 2010, Archives of internal medicine.

Empirical Performance of the Calibrated Self-Controlled Cohort Analysis Within Temporal Pattern Discovery: Lessons for Developing a Risk Identification and Analysis System

David Madigan, Martijn J Schuemie, Patrick B Ryan, 2013, Drug Safety.

Good practices for real‐world data studies of treatment and/or comparative effectiveness: Recommendations from the joint ISPOR‐ISPE Special Task Force on real‐world evidence in health care decision making

David Madigan, Wim Goettsch, Marc L. Berger, 2017, Pharmacoepidemiology and drug safety.

Empirical Performance of LGPS and LEOPARD: Lessons for Developing a Risk Identification and Analysis System

David Madigan, Martijn J Schuemie, Patrick B Ryan, 2013, Drug Safety.

Recommendations for Good Procedural Practices for Real-World Data Studies of Treatment Effectiveness and/or Comparative Effectiveness Designed to Inform Health Care Decisions: Report of the Joint ISPOR-ISPE Special Task Force on Real-World Evidence in Health Care Decision Making

Harold C. Sox, David Madigan, Wim Goettsch, 2017 .

Latent Class Mixture Models of Treatment Effect Heterogeneity

David Madigan, Zach Shahn, 2017 .

Sparse Bayesian Classifiers for Text Categorization ( U )

Wen-Hua Ju, David Madigan, David D. Lewis, 2003 .

Pooled analysis of rofecoxib placebo-controlled clinical trial data: lessons for postmarket pharmaceutical safety surveillance.

David Madigan, Harlan M Krumholz, D. Madigan, 2009, Archives of internal medicine.

Empirical Performance of a New User Cohort Method: Lessons for Developing a Risk Identification and Analysis System

David Madigan, Martijn J Schuemie, Ivan Zorych, 2013, Drug Safety.

Managing Data Quality for a Drug Safety Surveillance System

Patrick B. Ryan, J. Marc Overhage, Paul E. Stang, 2013, Drug Safety.

Bayesian methods for design and analysis of safety trials

David Madigan, David Manner, H Amy Xia, 2014, Pharmaceutical statistics.

Effective directed tests for models with ordered categorical data

David Madigan, Harold B. Sackrowitz, Arthur Cohen, 2003 .

Empirical Performance of a Self-Controlled Cohort Method: Lessons for Developing a Risk Identification and Analysis System

Patrick B. Ryan, Martijn J. Schuemie, David Madigan, 2013, Drug Safety.

A Learning Theory Framework for Association Rules and Sequential Events

Cynthia Rudin, David Madigan, Benjamin Letham, 2011 .

Discussion of "Least angle regression" by Efron et al

David Madigan, Greg Ridgeway, 2004 .

Empirical Performance of the Self-Controlled Case Series Design: Lessons for Developing a Risk Identification and Analysis System

David Madigan, Martijn J Schuemie, Marc A Suchard, 2013, Drug Safety.

An Evaluation of Three Signal-Detection Algorithms Using a Highly Inclusive Reference Event Database

David Madigan, Manfred Hauben, A. Lawrence Gould, 2009, Drug safety.

Bayesian Variable and Transformation Selection in Linear Regression

David Madigan, Adrian E Raftery, Jennifer A Hoeting, 2002 .

Learning From Epidemiology: Interpreting Observational Database Studies for the Effects of Medical Products

Patrick B. Ryan, Martijn J. Schuemie, David Madigan, 2013 .

A Flexible Bayesian Generalized Linear Model for Dichotomous Response Data with an Application to Text Categorization

David Madigan, Susana Eyheramendy, D. Madigan, 2007, 0708.0959.

Commentary: What Can We Really Learn From Observational Studies?: The Need for Empirical Assessment of Methodology for Active Drug Safety Surveillance and Comparative Effectiveness Research

David Madigan, Patrick Ryan, D. Madigan, 2011, Epidemiology.

A Note on Equivalence Classes of Directed Acyclic Independence Graphs

David Madigan, D. Madigan, 1993, Probability in the Engineering and Informational Sciences.

On the relation between conditional independence models determined by finite distributive lattices and by directed acyclic graphs

David Madigan, Christopher M. Triggs, Michael D. Perlman, 1995 .

Statistical Analysis of Clinical Variables to Predict the Outcome of Surgical Intervention in Patients with Knee Complaints

David Madigan, Greg Ridgeway, John W. O’Kane, 1999 .

Under-reporting of cardiovascular events in the rofecoxib Alzheimer disease studies.

David Madigan, Jerry Avorn, D. Madigan, 2012, American heart journal.

Empirical Performance of the Case–Control Method: Lessons for Developing a Risk Identification and Analysis System

David Madigan, Martijn J Schuemie, Patrick B Ryan, 2013, Drug Safety.

Detecting adverse drug reactions following long-term exposure in longitudinal observational data: The exposure-adjusted self-controlled case series

David Madigan, Martijn J Schuemie, Patrick B Ryan, 2016, Statistical methods in medical research.

A Hierarchical Model for Association Rule Mining of Sequential Events: An Approach to Automated Medical Symptom Prediction

Cynthia Rudin, David Madigan, Tyler H. McCormick, 2011 .

Interpreting observational studies: why empirical calibration is needed to correct p-values

William DuMouchel, David Madigan, Martijn J Schuemie, 2013, Statistics in medicine.

Evaluation of Disproportionality Safety Signaling Applied to Healthcare Databases

William DuMouchel, David Madigan, Martijn J Schuemie, 2013, Drug Safety.

Comprehensive comparative effectiveness and safety of first-line antihypertensive drug classes: a systematic, multinational, large-scale analysis

George Hripcsak, David Madigan, Martijn J Schuemie, 2019, The Lancet.

When should case‐only designs be used for safety monitoring of medical products?

David Madigan, Malcolm Maclure, Bruce Fireman, 2012, Pharmacoepidemiology and drug safety.

Drospirenone-containing oral contraceptives and venous thromboembolism: an analysis of the FAERS database

David Madigan, D. Madigan, Jennifer Shin, 2018, Open access journal of contraception.