Propensity score matching with time-dependent covariates

Biometrics. 2005 Sep;61(3):721-8. doi: 10.1111/j.1541-0420.2005.00356.x.


In observational studies with a time-dependent treatment and time-dependent covariates, it is desirable to balance the distribution of the covariates at every time point. A time-dependent propensity score based on the Cox proportional hazards model is proposed and used in risk set matching. Matching on this propensity score is shown to achieve a balanced distribution of the covariates in both treated and control groups. Optimal matching with various designs is conducted and compared in a study of a surgical treatment, cystoscopy and hydrodistention, given in response to a chronic bladder disease, interstitial cystitis. Simulation studies also suggest that the statistical analysis after matching outperforms the analysis without matching in terms of both point and interval estimations.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, U.S. Gov't, Non-P.H.S.
  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Cohort Studies
  • Computer Simulation
  • Cystitis, Interstitial / surgery
  • Cystoscopy
  • Data Interpretation, Statistical*
  • Female
  • Humans
  • Longitudinal Studies
  • Matched-Pair Analysis*
  • Proportional Hazards Models*
  • Urination