Real-World Evidence Analysis in R

What problem does it solve?

Enables researchers to design and emulate target trials using real-world data (RWD) to generate credible real-world evidence (RWE), addressing gaps in traditional randomized evidence with observational data.

Core Features & Use Cases

• Target trial emulation: specify eligibility, treatment strategies, follow-up, and outcomes to emulate a randomized trial using observational data.
• Propensity score methods: estimate and apply weights or matching to balance covariates between groups.
• External control arms: integrate external data sources to augment trial comparisons and enhance generalizability.
• Time-varying confounding: implement sequential trial emulation and marginal structural models to address dynamic treatment regimens.
• Survival and causal analyses: leverage survival models and causal inference techniques to estimate effects over time.
• Data quality and reporting: best practices for data quality checks and transparent reporting of RWE methods.

Quick Start

Load real-world data, configure a target trial emulation workflow, and run the TrialEmulation analyses to generate emulated trial results.