A Reading List on Statistics for Medical Decision Making

Glickman, Mark E., and Normand, Sharon-Lise T., "The Derivation of a Latent Threshold Instrumental Variables Model" (1995), Technical Report #HCP-1995-5, Dept of Health Care Policy, Harvard Medical School.

D. Heckerman. A tutorial on learning with Bayesian networks. Technical Report MSR-TR-95-06, Microsoft Research, March, 1995 (revised January, 1996).

94-17 Mueller, Peter and Rosner, Gary. "A Bayesian Population Model with Hierarchical Mixture Priors Applied to Blood Count Data"

95-06 Palmer, Judy L. and Mueller, Peter. "Bayesian Optimal Design in Population Models of Hematologic Data"

R. D. Shachter, S. K. Andersen and P. Szolovits. Global Conditioning for Probabilistic Inference in Belief Networks. Uncertainty in Artificial Intelligence 94. Morgan Kaufmann. 514-522, 1994. (postscript)

94-22 Stangl, Dalene K. "Prediction and Decision Making Using Bayesian Hierarchical Models"

95-32 Stangl, Dalene. "Bayesian Methods in the Analysis of Clinical Trials: A Discussion"

95-01 Stangl, Dalene K. and Greenhouse, Joel B. "Assessing Placebo Response Using Bayesian Hierarchical Survival Models"

P. Szolovits. Knowledge-Based Systems. In A. R. Meyer, et al., editors, Research Directions in Computer Science: An MIT Perspective, pages 317-370, MIT Press, 1991. (postscript)

P. Szolovits. Uncertainty and Decisions in Medical Informatics. Methods of Information in Medicine, 34:111-21, 1995. (postscript)

P. Szolovits and S. P. Pauker. Pedigree Analysis for Genetic Counseling. In Lun, K. C., et al. (eds.), MEDINFO 92: Proceedings of the Seventh Conference on Medical Informatics, pages 679-683. Elsevier (North Holland) 1992. (postscript)

P. Szolovits and S. G. Pauker. Categorical and Probabilistic Reasoning in Medicine Revisited. Artificial Intelligence 59:167-180, 1993.

94-23 West, Mike. "Hierarchical mixture models in neural transmission analysis"