Cardinality matching versus propensity score matching for addressing cluster-level residual confounding in implantable medical device and surgical epidemiology: a parametric and plasmode simulation study.

ABSTRACT:

Background

Rapid innovation and new regulations lead to an increased need for post-marketing surveillance of implantable devices. However, complex multi-level confounding related not only to patient-level but also to surgeon or hospital covariates hampers observational studies of risks and benefits. We conducted parametric and plasmode simulations to compare the performance of cardinality matching (CM) vs propensity score matching (PSM) to reduce confounding bias in the presence of cluster-level confounding.

Methods

Two Monte Carlo simulation studies were carried out: 1) Parametric simulations (1,000 iterations) with patients nested in clusters (ratio 10:1, 50:1, 100:1, 200:1, 500:1) and sample size n = 10,000 were conducted with patient and cluster level confounders; 2) Pla

SUBMITTER: Du M 

PROVIDER: S-EPMC11583411 | biostudies-literature | 2024 Nov

REPOSITORIES: biostudies-literature