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Incorporating Correlation for Multivariate Failure Time Data When Cluster Size Is Large
Sunday, May 30, 2010 - 3:15pm

Portland State University
Fariborz Maseeh Department of Mathematics & Statistics

The Maseeh Mathematics and Statistics Colloquium Series presents*

Lan Xue
Department of Statistics,
Oregon State University

Incorporating Correlation for Multivariate Failure Time Data When Cluster Size Is Large

Abstract: We propose a new estimation method for multivariate failure time data using the quadratic inference function (QIF) approach. The proposed method efficiently incorporates within-cluster correlations. Therefore it is more efficient than those which ignore within-cluster correlation. Furthermore, the proposed method is easy to implement. Unlike the weighted estimating equations in Cai and Prentice (1995), it is not necessary to explicitly estimate the correlation parameters. This simplification is particularly useful in analyzing data with large cluster size where it is difficult to estimate intracluster correlation. Under certain regularity conditions, we show the consistency and asymptotic normality of the proposed QIF estimators. A Chi-squared test is also developed for hypothesis testing. We conduct extensive Monte Carlo simulation studies to assess the finite sample performance of the proposed methods. We also illustrate the proposed methods by analyzing a data set from a kidney infection study.

Friday, April 30th, 2010, 3:15pm
Neuberger Hall Room 381
(Refreshments served at 3:00 in Neuberger Hall Room 344)

* Sponsored by the Maseeh Mathematics and Statistics Colloquium Series Fund and the Fariborz Maseeh Department of Mathematics & Statistics, PSU. This event is free and open to the public.