Imputation of Censored Response Data in a Bivariate Designed Experiment

ABSTRACT

Imputation of censored response data in bivariate experiments with correlated responses has not been adequately addressed in the current literature. In this article, we show several ways of handling and imputing censored response data in bivariate designed experiments. This article introduces an imputation method for censored response data in designed experiments using the conditional expectation of the relevant truncated distribution. The method takes into consideration the dependency as well as the multivariate nature of the response variables. A numerical example is presented. Variations of the method are presented and imputed values are compared with each other and the original data.

KEYWORDS:

• censored data
• conditional expectation
• design of experiment
• imputation
• truncated distribution

ACKNOWLEDGEMENT

Funding in support of this work was provided by the Pacific Institute for the Mathematical Sciences (PIMS), Nortel Networks, the Natural Sciences and Engineering Research Council (NSERC) of Canada. The first author conducted this research while he was PIMS industrial post-doctoral fellow at the StatCAR Lab of the Mathematics and Statistics Department of the University of Calgary. He is also indebted to the National Science Foundation (NSF) of USA for their support (Grant#DMS-0207059).

The authors are grateful to the reviewers for their most valuable and helpful comments which clarified some of the ambiguities of the earlier version.