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Events

Research Luncheon Workshop Series:
Statistical Methods for Advancing the Research Agenda

March 30, 2005
11:30 – 2:00
391 Speakman Hall (CSPD)

RSVP by March 23 to Julie Fesenmaier
juliefes@temple.edu

Presenters:

Francis Hsuan, Ph.D.
Department of Statistics
" Bridging Correspondence Analysis and Poisson Regression"
Both Correspondence Analysis and Poisson Regression are useful tools to analyze categorical data. The theory (singular value decomposition, generalized linear model) and practice of each method have been well documented. In this talk, we illustrate both approaches using a published set of marketing survey data, and then compare the two approaches. We will also explore the possibility of combining the two methods in one framework.

Damaraju Raghavarao, Ph.D.
Chair, Department of Statistics
"Planning of Choice Experiments"
Several factors (or, attributes) contribute in choosing a product or procedure. If the attributes are related to benefits/costs, one looks for maximum benefits and minimum costs. However some trade-offs are needed . Conjoint analysis using fractional factorial experiments are commonly used for this purpose and in the widely used choice sets, dominating or dominated profiles may occur. We are proposing methodology avoiding dominated and dominating profiles. We will also discuss the exchange rate for the attributes.

Sanat Sarkar, Ph.D.
Department of Statistics
" A New Approach to Controlling Type I Errors in Simultaneous Testing of a Large Number of Hypotheses"
A new statistical measure, known as the FDR (False Discovery Rate), providing an overall Type I error rate in simultaneous testing of a number of hypotheses was introduced in 1995. Statistical methods controlling this measure are more powerful than the traditional methods. Although it is now one of the most commonly used statistical ideas in modern gene-related research, it has the potential to be useful in any statistical investigation involving large number of hypotheses.