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Robust Estimation in AFT Models and a Covariate Adjusted Mann–Whitney Statistic for Comparing Two Sojourn Times

  • Sutirtha Chakraborty
  • Somnath DattaEmail author
Conference paper
Part of the Springer Proceedings in Mathematics & Statistics book series (PROMS, volume 175)

Abstract

A Mann–Whitney statistic may be used to compare two sets of state waiting times; however, wrong conclusions may be reached if there are confounding covariates. We develop a Mann–Whitney type test statistic based on the residuals from an accelerated failure time model fitted to two groups of sojourn times with a common set of covariates. This covariate adjusted test statistics handles right censoring via the inverse probability of censoring weights. These weights were devised to improve efficiency in the sense that certain pairs in which at least one state entry time is uncensored could be compared. Extensive simulation studies were undertaken to evaluate the performance of this test. A real data illustration of our methodology is also provided.

Keywords

Confounding U-statistic Two sample Sojourn time AFT model 

Notes

Acknowledgments

This research was supported in parts by grants from the US National Science Foundation (DMS-0706965) and the National Security Agency (H98230-11-1-0168). Chakraborty acknowledges fellowship support and a dissertation completion award from University of Louisville. The authors thank an anonymous reviewer for helpful comments; they also thank the Christopher and Dana Reeve Foundation and all current and past members of the NeuroRecovery Network.

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.National Institute of Biomedical GenomicsKalyaniIndia
  2. 2.University of FloridaGainesvilleUSA

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