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Communications in Statistics - Simulation and Computation Volume 48, 2019 - Issue 10
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Original Articles

Performance of standard imputation methods for missing quality of life data as covariate in survival analysis based on simulations from the International Breast Cancer Study Group Trials VI and VII*

Marion ProcterFrontier Science (Scotland) Ltd, Kingussie, UK; Correspondence[email protected]
&
Chris RobertsonDepartment of Mathematics and Statistics, University of Strathclyde, Glasgow, UK
Pages 3063-3077 | Received 24 Nov 2016, Accepted 01 May 2018, Published online: 13 Aug 2018

References

  • Coates, A. S., C. Hürny, H. F. Peterson, J. Bernhard, M. Castiglione-Gertsch, R. D. Gelber, and A. Goldhirsch; for the International Breast Cancer Study Group. 2000. Quality-of-life scores predict outcome in metastatic but not early breast cancer. Journal of Clinical Oncology 18 (22):3768–74. doi:10.1200/JCO.2000.18.22.3768.
  • Curran, D. 2000. Analysis of incomplete longitudinal data. PhD. diss., Linsburg Universitair Centrum, as cited in Fairclough, D.L. (2010). Design and analysis of quality of life studies in clinical trials. 2nd ed. Boca Raton, FL: Chapman and Hall.
  • Epplein, M., Y. Zheng, W. Zheng, Z. Chen, K. Gu, D. Penson, W. Lu, and X.-O. Shu. 2011. Quality of life after breast cancer diagnosis and survival. Journal of Clinical Oncology 29 (4):406–12. doi:10.1200/JCO.2010.30.6951.
  • Fairclough, D. L. 2010. Design and analysis of quality of life studies in clinical trials. 2nd ed. Boca Raton, FL: Chapman and Hall.
  • Kenne Sarenmalm, E., A. Odén, J. Öhlén, F. Gaston-Johansson, and S. B. Holmberg. 2009. Changes in health-related quality of life may predict recurrent breast cancer. European Journal of Oncology Nursing 13:323–9. doi:10.1016/j.ejon.2009.05.002.
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  • MacKenzie, T., and M. Abrahamowicz. 2002. Marginal and hazard ratio specific random data generation: Applications to semi-parametric bootstrapping. Statistics and Computing 12:245–52. doi:10.1023/A:1020750810409.
  • Molenberghs, G., and M. G. Kenward. 2007. Missing data in clinical studies. Chichester, UK: Wiley.
  • Procter, M. J. 2016. Influence of missing explanatory variables and longitudinal assessments in breast cancer clinical trials. PhD. diss., University of Strathclyde.
  • Procter, M., and C. Robertson. 2017. Imputing missing quality of life data as covariate in survival analysis of the international Breast Cancer Study Group Trials VI and VII. Communications in Statistics - Simulation and Computation. doi:10.1080/03610918.2017.1390123.
  • Rubin, D. B. 1976. Inference and missing data. Biometrika 63 (3):581–92. doi:10.1093/biomet/63.3.581.
  • Rubin, D. B. 1987. Multiple imputation for non-response in surveys. New York, NY: Wiley.
  • White, I. R., P. Royston, and A. M. Wood. 2011. Multiple imputation using chained equations: issues and guidance for practice. Statistics in Medicine 30 (4):377–99. doi:10.1002/sim.4067.

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