JASA Highlights
A Peek at the December Issue
David L. Banks, Len stefanski, and Dalene stangl
T
he Applications & Case Studies section
starts with a discussion paper by Rob
A Message from the Editor
Scharpf, Håkon Tjelmeland, Giovanni
Parmigiani, and Andrew Nobel titled “A Bayesian David Banks
Model for Cross-Study Differential Gene
Expression.” There are two discussions, one by
It is an unalloyed delight to report that the December issue of
Debashis Ghosh and Hyungwon Choi and the
JASA is the last of my editorial duties. I have certainly enjoyed
other by Xiaodan Fan and Jun Liu. this job, but it is relentless and wears one down over time. I am
The section fills out with “Analysis of Multifactor
deeply and completely grateful to the associate editors,
Affine Yield Curve Models,” by Sid Chib and
whose unflagging service makes JASA so outstanding; to the
Bakhodir Ergashev; “Bayesian Calibration of
Microsimulation Models,” by Caroline Rutter,
insufficiently thanked referees, who do most of the hard
Diana Miglioretti, and Jim Savarino; “Option-
work; and to the AsA staff, whose support has made this
Pricing with Model-Guided Nonparametric
journal possible. It has been a wonderful ride, and I’m very
Methods,” by Jianqing Fan and Loriano
glad it is over.
Mancini; “Semi-Parametric Efficient Estimation
for Incomplete Longitudinal Binary Data with I’d like to thank the authors, too. Partly I thank them for the
Application to Smoking Trends,” by Jamie Perin,
quality of their work, but even more for their professionalism
John Preisser, and Paul Rathouz; and “Modeling
and collegiality. Reviewing is an imperfect process, despite the
and Inference for Measured Crystal Orientations
best will in the world and a sincere desire on the part of all
and a Tractable Class of Symmetric Distributions for
Rotations in 3 Dimensions,” by Melissa Bingham,
parties to find the good, rather than nit-pick the bad. It is an
Daniel Nordman, and Steve Vardeman.
asymmetric relationship, and few authors feel entirely well used
and fully appreciated. Despite these difficulties, I treasure the
Theory and Methods
uniformly positive and constructive interactions I have been
Paul R. Rosenbaum and Jeffrey H. Silber lead the
lucky to enjoy.
section with “Amplification of Sensitivity Analysis
in Matched Observational Studies,” wherein they
I have no concerns for the future of JASA; Hal stern, Len
develop methods for assessing the impact of an
stefanski, and Dalene stangl have it well in hand. In the words
unobserved covariate not controlled for match-
ing. For Bayesians at heart, Y. Chung and D. B.
stephen Vincent Benét attributes to Daniel webster’s nameless
Dunson use a probit stick-breaking process to
interlocutor regarding the united states, JASA “stands as she
develop a methodology for flexibly characterizing stood, rock-bottomed and copper-sheathed.” It is one of the
the relationship between a response and multiple
great journals in statistics and deserves its prominence in the
predictors in “Nonparametric Bayes Conditional
history of our profession.
Distribution Modeling with Variable Selection.”
Mr. Rogers knows you can learn a lot from your
neighbors and so do R. V. Craiu, J. Rosenthal, and Factor Model Approach to Multiple Testing Under
C. Yang. In “Learn from Thy Neighbor: Parallel- Dependence” by C. Friguet, M. Kloareg, and D.
Chain and Regional Adaptive MCMC,” these Causeur. A. Gandy’s “Sequential Implementation
authors address the problem of adapting MCMC of Monte Carlo Tests with Uniformly Bounded
samplers to multi-modal distribution. Resampling Risk” introduces an open-ended
From multiple modes to multiple haystacks, sequential algorithm for computing the p-value of
“Simultaneous Testing of Grouped Hypotheses: a test using Monte Carlo simulation that guaran-
Finding Needles in Multiple Haystacks” by T. T. tees the resampling risk is uniformly bounded by an
Cai and W. Sun develops a compound decision arbitrarily small constant. D. Paindaveine studies
theoretic framework for testing grouped hypotheses two types of multivariate runs—an elliptical exten-
and introduces an oracle procedure that minimizes sion of spherical runs and a new notion of matrix-
the false nondiscovery rate subject to a constraint on valued runs—in “On Multivariate Runs Tests for
the false discovery rate. The impact of dependence Randomness.” The Food and Drug Administration
among multiple test statistics is the topic of “A will soon issue guidance on multiple endpoints.
December 2009 AmstAt News 25
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