[Cowystats] CO/WY ASA Spring meeting information

Matt Pocernich pocernic at rap.ucar.edu
Wed Apr 11 12:20:19 MDT 2007

### Details on Spring Meeting (April 20th)
### Rick Katz Talk at School of Mines (April 27th)
### Job Opportunity Scientist II Fair Issac.

### Chapter Spring Meeting Friday April 20th
### National Center for Atmospheric Research Mesa Lab, Boulder

Once again the Spring Chapter meeting is being held at the National
Center for Atmospheric Research's beautiful NCAR lab.  Located in the
hills above Boulder, the setting for the meeting is alone worth the
trip.  More details about the lab are at
http://eo.ucar.edu/what/arch1.html .  We have talks covering a wide
variety of topics.  This reflects the wide variety of interests within
our group.  Again, if you are interested there is a tour of the Vislab
prior to the beginning of the talks.  Beautiful weather guaranteed. 

Tentative Schedule

8:45 - 9:30             Coffee and Refreshments
9 - 9:30                Vislab Tour
9:30 - 9:45     	Welcome
9:45-10:15      	Ben Houston     Statistical Process Control
10:15-10:30     	Yu Yang (CSU)   Estimation for Non-negative 
	Levy-driven Ornstein-Uhlenbeck Processes
10:30-10:45     Bo Li (GSP)     
	The ``Hockey Stick" and the 1990s: A
	Statistical Perspective on Reconstructing Hemispheric Temperatures 
10:45 - 11:15   Break
11:15-12:00     Kari Caufman (UNC- SAMSI)
	Covariance Tapering for Likelihood Based  Estimation in Large 
		Spatial Datasets
12:00-12:15     Sonya Heltshe (UCHS)     
		Length-biased sampling in cancer screening with
			variable test sensitivity
12:15-1:15      Lunch
115-130 C       Chapter Activities
130-2:15        Hari Iyer (CSU)         
	Fiducial Inference of R. A. Fisher -- History, Applications, 
		and Generalizations
215-230         Brandi Wagner - Health Science  
	Permutation Based Adjustments for the Significance of Partial
	Regression Coefficients in Microarray Data Analysis 
230-245         Mark Labovitz (CU - Denver)     
	Simulating the Behavior of Target Maturity Funds 
245-3           Break
3-315           Ashlyn Hutchinson (Mines)       
	A Comparison of Methods to Determine Bioequivalence of Topical
		Dermatological Drug Products
3:15 - 4        Brian Wien (Gilead)             
	Multiple Comparisons in Clinical Trials for Regulatory Purposes 
4 - 5           Reception - beer and wine.


Directions to the Mesa lab are found below.  Also note that NCAR runs
a shuttle service that connects with RTD buses.  Contact me for
further details.  


Selected Abstracts

Multiple Comparisons in Clinical Trials for Regulatory Purposes: A
Brief Overview with Discussion  

Brian L. Wiens 
Gilead Colorado, Inc. 

We consider the problem of multiple hypothesis tests in clinical
trials aimed at supporting regulatory approval of a new medical
therapeutic. Sponsors (generally pharmaceutical companies) must plan a
multiple comparison procedure that allows for precise differentiation
of an investigational product compared to placebo. This often begins
with specification of one or more primary endpoints, one or more
secondary endpoints, etc. This can be complicated by the use of
multiple treatment groups such as multiple doses or multiple regimens
of the investigational product. The current trend seems to be toward
using more complicated study designs due to factors such as increased
sophistication of clinical trial specialists and a desire for faster,
more efficient drug development. We discuss the regulatory hurdles and
some ways that statisticians are approaching them, including some
state-of-the-art procedures for handling multiple comparisons such as
fallback, gatekeeping and tree-structured tests.  

Covariance Tapering for Likelihood Based Estimation in Large Spatial
Cari Kaufman, Statistical and Applied Mathematical Sciences Institute
(SAMSI) and National Center for Atmospheric Research (NCAR)  

Likelihood-based methods such as maximum likelihood, REML, and
Bayesian methods are attractive approaches to estimating covariance
parameters in spatial models based on Gaussian processes. Finding such
estimates can be computationally infeasible for large datasets,
however, requiring O(n^3) calculations for each evaluation of the
likelihood based on n observations. I will discuss the method of
covariance tapering to approximate the likelihood in this setting.  In
this approach, covariance matrices are ``tapered,'' or multiplied
element-wise by a compactly supported correlation matrix.  This
produces matrices which can be be manipulated using more efficient
sparse matrix algorithms.  I will present two approximations to the
Gaussian likelihood using tapering and discuss the asymptotic behavior
of estimators maximizing these approximations.  I will also present an
example of using the approximations in a Bayesian model for the
climatological (long-run mean) temperature difference between two sets
of output from a computer model of global climate, run under two
different land use scenarios.  

Fiducial Inference of R. A. Fisher -- History, Applications, and

Hari Iyer, Department of Statistics, Colorado State University 

R. A. Fisher introduced the FIDUCIAL ARGUMENT which he used to derive
confidence intervals for the difference between two normal means when
the variances are unequal -- the so called Behrens-Fisher problem. He
also used this approach to derive interval estimates in several other
situations. However his contemporaries found a number of shortcomings
with the fiducial method. It is safe to say that the fiducial method
eventually fell into disfavor among statisticians. Recently the
fiducial method appears to be enjoying a revivial of sorts. In this
talk I will give a brief overview of the history of fiducial
inference, give examples and applications of the fiducial argument,
and discuss recent generalizations that makes the fiducial approach a
powerful tool for deriving inference procedures. Asymptotic
properties  and small sample simulations confirm that fiducial
procedures have excellent operating characteristics in general. [Based
on joint work with my colleagues Jan Hannig, Jack Wang, and several
former and current PhD students from the department of statistics at
Colorado state university].  

### Rick Katz Seminar at School of Mines Friday April 27th
"Assessing the quality and economic value of weather and climate forecasts"
3:00 pm in Chauvenet Hall 143,
For further information see


Much of the research on evaluating the quality and economic value of
imperfect information, such as forecasts, has been either performed
within the meteorological community or at least motivated by
meteorological applications. Perhaps the most noteworthy aspect is the
ability to produce well-calibrated probabilistic weather forecasts,
through a variety of objective and subjective approaches. I will point
out some connections to statistics, including the concept of
sufficiency. I will also present some valuation puzzles, illustrating
why it is so difficult to draw any general conclusions about the
economic value of weather and climate forecasts.


Richard W. Katz is a Senior Scientist in the Institute for Study of
Society and Environmental, National Center for Atmospheric Research,
Boulder. He received a Ph.D. in statistics from Pennsylvania State
University in 1974. He was one of the founders of NCAR's Geophysical
Statistics Project. His current interests include the application of the
statistical theory of extreme values to climate change.
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Matt Pocernich
National Center for Atmospheric Research
Research Applications Laboratory
(303) 497-8312

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