A sensitivity analysis for causal parameters in structural proportional hazards models

• Autores: E. Goetghebeur, T. Loeys
• Localización: Sort: Statistics and Operations Research Transactions, ISSN 1696-2281, Vol. 27, Nº. 1, 2003, págs. 31-40
• Idioma: inglés
• Títulos paralelos:
  • Un análisis de sensibilidad para parámetros causales en modelos de riesgos estructurales proporcionales
• Enlaces
  • Texto completo (pdf)
• Resumen

  • Deviations from assigned treatment occur often in clinical trials. In such a setting, the traditional intent-to-treat analysis does not measure biological efficacy but rather programmatic effectiveness. For all-or-nothing compliance situation, Loeys and Goetghebeur (2003) recently proposed a Structural Proportional Hazards method. It allows for casual estimation in the complier subpopulation provided the exclusion restriction holds: randomization per se has no effect unless exposure has changed. The asumption is typically made with structural models for noncompliance but questioned when the trial is not blinded. In this paper we extend the structural PH model to allow for an effect of randomization per se. This enables analyzing sensitivity of conclusions to deviations from the exclusion restriction. In a colo-rectal cancer trial we find the causal estimator for the effect of an arterial device implantation to be remarkably insensitive to such deviations.

• Referencias bibliográficas
  • Barlow, R.E., Bartholomew, D.J., Bremner, J.M. and Brunk, H.D. (1972). Statistical Inference under Order Restrictions. New York: Wiley.
  • Efron, B. (1981). Censored data and the bootstrap. Journal of the American Statistical Association, 76, 312-319.
  • Frangakis, C. and Rubin, D. (1999). Addressing complications of intention-to-treat analysis in the combined presence of all-or-none treatment...
  • Imbens, G. and Rubin, D. (1997). Bayesian inference for causal effects in randomized experiments with noncompliance. Annals of Statistics,...
  • Hernßn, M.A., Brumback, B. and Robins, J.M. (2000). Marginal structural models to estimate the causal effect of zidovudine on the survival...
  • Kemeny, M.M., Adak, S., Gray, B., Macdonald, J.S., Smith, T., Lipsitz, S., Sigurdson, E.R., O’Dwyer, P.J. and Benson, A.B. (2002). Combined-modality...
  • Loeys, T. and Goetghebeur, E. (2003). A causal proportional hazards estimator for the effect of treatment actually received in a randomized...
  • Loeys, T. and Goetghebeur, E. (2002). Causal proportional hazards models for the effect of treatment actually received in a randomized trial...
  • Pearl, J. (2002). Causal inference in the health sciences: a conceptual introduction. InHealth Ser. Outcomes Res. Method (in press).
  • Robins, J.M. and Tsiatis, A.A. (1991). Correcting for noncompliance in randomized trials using rank preserving structural failure time models....
  • Robins, K.M. and Greenland, S. (1994). Adjusting for differential rates of prophylaxis for PCP in highversus low-dose AZT treatment arms in...
  • Scharfstein, D. (2002). Frequentist and bayesian inference for potentially non-ignorable non-response in randomized clinical trials. Proceedings...
  • Sun, J. and Kalbfleisch, J.D. (1993). The analysis of current status data on point processes. Journal of the American Statistical Association,...