Non‐parametric analysis of treatment—covariate interaction in the presence of censoring

Non‐parametric analysis of treatment—covariate interaction in the presence of censoring The demonstration of varying treatment efficacy among different subsets of patients is an important part of the analysis of clinical trials. The paper commences by clarifying the meaning of interaction and by reviewing valid procedures of analysis in the presence of interaction. Suitable descriptive measures of treatment—covariate interactions are (ratios of) hazard ratios to which generalized Patel—Hoel tests for qualitative or ordinal categorical covariates are related. Both the hazard ratios and the tests are given in a formulation for use with different scoring systems such as u‐ or e. Furthermore, the procedures are related to common k‐sample tests and thus are suitable for proportional and for converging hazards. A worked example is included. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Statistics in Medicine Wiley

Non‐parametric analysis of treatment—covariate interaction in the presence of censoring

Statistics in Medicine, Volume 7 (12) – Dec 1, 1988

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Publisher
Wiley
Copyright
"Copyright © 1988 Wiley Subscription Services, Inc., A Wiley Company"
ISSN
0277-6715
eISSN
1097-0258
D.O.I.
10.1002/sim.4780071206
Publisher site
See Article on Publisher Site

Abstract

The demonstration of varying treatment efficacy among different subsets of patients is an important part of the analysis of clinical trials. The paper commences by clarifying the meaning of interaction and by reviewing valid procedures of analysis in the presence of interaction. Suitable descriptive measures of treatment—covariate interactions are (ratios of) hazard ratios to which generalized Patel—Hoel tests for qualitative or ordinal categorical covariates are related. Both the hazard ratios and the tests are given in a formulation for use with different scoring systems such as u‐ or e. Furthermore, the procedures are related to common k‐sample tests and thus are suitable for proportional and for converging hazards. A worked example is included.

Journal

Statistics in MedicineWiley

Published: Dec 1, 1988

Keywords: ; ; ; ; ; ; ;

References

  • Patient subsets and variation in therapeutic efficacy
    Simon, R.
  • Assessing apparent treatment‐covariate interactions in randomized clinical trials
    Byar, D. P.
  • Factorial designs for randomized clinical trials
    Byar, D. P.; Piantadosi, S.
  • Estimation of the hazards ratio in two grouped samples
    Moreau, T.; Le Minor, M.; Myquel, P.; Lellouch, J.

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