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Activity Number: 431
Type: Topic Contributed
Date/Time: Wednesday, August 5, 2009 : 8:30 AM to 10:20 AM
Sponsor: IMS
Abstract - #304746
Title: Testing the Regression Coefficient for High-Dimensional Data
Author(s): Pingshou Zhong*+ and Song Xi Chen
Companies: Iowa State University and Iowa State University
Address: 210 Snedecor Hall, Ames, IA, 50011,
Keywords: High Dimensional Data ; F-test ; Regression coefficient
Abstract:

We proposed a new test statistic for testing the coefficients in a simple regression model with high dimensional covariates. It can be applied to ``large p, small n" cases, where the usual F-test for testing the coefficient does not work. From the simulation study, we found that the proposed test had better power than the usual F-test while it can preserve the size of the type I error well when the dimension of the covariate approach the sample size. However, when the dimension of the covariate is much smaller than the sample size, F-test is more powerful to detect the departure from the null hypothesis. Therefore, we suggested combining F-test and our proposed test together to test coefficient in regression models. We applied the proposed test procedure to a microarray data set.

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