title: Propensity score matching with time-dependent covariates.
abstract: 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.
authors.affiliation: Center for Statistical Sciences, Brown University, Providence, Rhode Island 02912, USA. bolu@stat.brown.edu
authors.forename: Bo
authors.initials: B
authors.lastname: Lu
mesh_terms: D015331:Cohort Studies; D003198:Computer Simulation; D018856:Cystitis, Interstitial / Q000601:surgery; D003558:Cystoscopy; D003627:Data Interpretation, Statistical; D005260:Female; D006801:Humans; D008137:Longitudinal Studies; D016555:Matched-Pair Analysis; D016016:Proportional Hazards Models; D014554:Urination