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Microarrays (Basel, Switzerland)|September 9, 2016
Comparative Analysis of Biologically Relevant Response Curves in Gene Expression Experiments: Heteromorphy, Heterochrony, and HeterometryStuart G BakerMedical Decision Making : an International Journal of the Society for Medical Decision Making|October 14, 2017
Simple Decision-Analytic Functions of the AUC for Ruling Out a Risk Prediction Model and an Added PredictorStuart G BakerMedical Decision Making : an International Journal of the Society for Medical Decision Making|January 20, 2019
Cancer Screening Markers: A Simple Strategy to Substantially Reduce the Sample Size for ValidationStuart G BakerJournal of the National Cancer Institute|July 4, 2009
Improving the biomarker pipeline to develop and evaluate cancer screening testsStuart G BakerStatistics in Medicine|May 11, 2013
Causal inference, probability theory, and graphical insightsStuart G BakerBMC Bioinformatics|September 10, 2010
Simple and flexible classification of gene expression microarrays via Swirls and RipplesStuart G BakerStatistical Applications in Genetics and Molecular Biology|May 2, 2006
A simple loglinear model for haplotype effects in a case-control study involving two unphased genotypesStuart G BakerJournal of the National Cancer Institute|October 22, 2009
Putting risk prediction in perspective: relative utility curvesStuart G BakerEmerging Themes in Epidemiology|March 25, 2020
Latent class instrumental variables and the monotonicity assumptionStuart G BakerBiometrics|May 16, 2007
Estimating lead time and overdiagnosis associated with PSA screening from prostate cancer incidence trendsDonatello Telesca, Ruth Etzioni, Roman GulatiPageof 26