Madigan, D., Mittal, S., and Roberts, F. (2008). Efficient sequential decision making algorithms for container inspection operations. Under revision.
Cheng, J. and Madigan, D. (2008). Bayesian Approaches to Aspects of the Vioxx Trials: Non-ignorable Dropout and Sequential Meta-Analysis. Submitted.
Hauben, M., Madigan, D., Reisinger, S., Hochberg, A., and O'Hara, D. (2008). Effects of Stratification on Three Pharmacovigilance Data Mining Algorithms. Submitted.
Balakrishnan, S. and Madigan, D. (2009). Priors on the variance in sparse Bayesian learning: the demi-Bayesian lasso. Submitted.
Ross, J.S., Madigan, D., Kill, 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. Annals of Internal Medicine, to appear.
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., O'Hara, 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., O'Hara, 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.
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 Screening the WHO global drug safety database. Submitted.
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, to appear