Rank Tests for Multivariate Linear Models in the Presence of Missing Data

  • Lee, Jae-Won (Department of Statistics, Korea University, Seoul 136-701) ;
  • David M. Reboussin (Department of Public Health Sciences, Bowman Gray School of Medicine, Winston Salem, NC 27157, USA)
  • Published : 1997.09.01

Abstract

The application of multivariate linear rank statistics to data with item nonresponse is considered. Only a modest extension of the complete data techniques is required when the missing data may be thought of as a random sample, and an appropriate modification of the covariances is derived. A proof of the asymptotic multivariate normality is given. A review of some related results in the literature is presented and applications including longitudinal and repeated measures designs are discussed.

Keywords

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