Parameter Recovery Checker

What problem does it solve?

Parameter Recovery Checker guides researchers to validate identifiability of computational cognitive models by evaluating how well true parameters can be recovered from simulated data, guarding against misinterpretation of fitted values.

Core Features & Use Cases

• Define the parameter space and ground-truth values, ensuring coverage across plausible ranges.
• Simulate data with a fixed model, fit the same model to recover parameters, and compute recovery metrics (r, bias, RMSE).
• Evaluate model recoverability and parameter tradeoffs; plan data collection accordingly.
• Use in planning experiments, validating novel models, or auditing analyses before reporting results.

Quick Start

Prepare ground-truth parameter values and run the parameter-recovery pipeline against your model to assess identifiability.