


Stuart G. Baker, ScD
Mathematical Statistician Biometry Research Group
Location 
Division of Cancer Prevention National
Cancer Institute 9609 Medical Center Drive, Room 5E638
Rockville, MD 20850 
Phone 
(240) 2767147 

Fax 
(240) 2767845 
Email 
bakers@mail.nih.gov 
Dr. Stuart G. Baker (sb16i@nih.gov) develops statistical methods with applications in biology and medicine and also writes commentaries on theories of carcinogenesis. Examples include:
 the concept of "paradigm instability," based on a buried treasure analogy, (Baker et. al. 2010, Baker 2013) for discussing somatic mutation theory versus the tissue organization field theory of carcinogenesis;
 the paired availability design for historical controls, which adjusts for different availabilities of treatment in different centers using a principal stratification model independently developed by Permutt and Hebel (1989), Baker and Lindeman (1994), Angrist, et al. (1996);
 the multinomialPoisson transformation for easily computing variances of saturated multinomial distributions (Baker,1994);
 composite linear models for analyzing categorical data subject to ignorable or nonignorable missing data mechanisms (1994);
 the BKPlot for illustrating mixtures of probabilities, independently developed for Simpson's paradox by Tan (1986), Jeon et. al. (1987), and Baker and Kramer (2001) and also applied to the Prentice Criterion for surrogate endpoints (Baker, 2013);
 relative utility curves for evaluating risk prediction via decision analysis (Baker et al, 2009, Baker et al. 2012);
 Swirls and Ripples, a centroidbased analysis that can include "islands" of one class within another class, called Swirls, or the usual curved boundaries, called Ripples (Baker, 2010);
 a leaveoneout approach for evaluating surrogate endpoints (Baker et. al. 2012);
 a biomarker pipeline to develop and evaluate cancer screening tests (Baker 2009);
 a latentclass model for the genetic analysis of twin data (Baker et. al. 2005), which is a major improvement over the usual variance components model involving heritability;
 a method to compare biologically relevant response curves in gene expression experiments in terms of heteromorphy, heterochrony, and heterometry (Baker 2014).
Dr. Baker was the first recipient of the distinguished alum award from the Department of Biostatistics at the Harvard School of Public Health. He is also a fellow of the American Statistical Association and an elected member of the International Statistical Institute.
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